diff --git a/translations/README-ur.md b/translations/README-ur.md index 950a5dc..0e71a77 100644 --- a/translations/README-ur.md +++ b/translations/README-ur.md @@ -13,13 +13,21 @@
ترجمہ: - + - [中文版本](translations/README-cn.md) - [Tiếng Việt - Vietnamese](translations/README-vi.md) - [Español](translations/README-es.md) - [Português Brasileiro](translations/README-ptbr.md) - [Polish](translations/README-pl.md) -- [Urdu](translations/README-ur.md) +- [繁體中文](translations/README-tw.md) +- [Japanese (日本語)](translations/README-ja.md) +- [Russian](translations/README-ru.md) +- [German](translations/README-de.md) +- [Bahasa Indonesia](translations/README-id.md) +- [ខ្មែរ - Khmer](translations/README-kh.md) +- [Uzbek](translations/README-uz.md) +- [Bulgarian](translations/README-bg.md) +- [বাংলা - Bangla](translations/README-bn.md)
@@ -27,19 +35,18 @@ - [हिन्दी](https://github.com/jwasham/coding-interview-university/issues/81) - [עברית](https://github.com/jwasham/coding-interview-university/issues/82) -- [Bahasa Indonesia](https://github.com/jwasham/coding-interview-university/issues/101) - [Arabic](https://github.com/jwasham/coding-interview-university/issues/98) - [Turkish](https://github.com/jwasham/coding-interview-university/issues/90) - [French](https://github.com/jwasham/coding-interview-university/issues/89) -- [Russian](https://github.com/jwasham/coding-interview-university/issues/87) -- [Ukrainian](https://github.com/jwasham/coding-interview-university/issues/106) +- [Українська](https://github.com/jwasham/coding-interview-university/issues/106) - [Korean(한국어)](https://github.com/jwasham/coding-interview-university/issues/118) - [Telugu](https://github.com/jwasham/coding-interview-university/issues/117) -- [Urdu](https://github.com/jwasham/coding-interview-university/issues/140) - [Thai](https://github.com/jwasham/coding-interview-university/issues/156) - [Greek](https://github.com/jwasham/coding-interview-university/issues/166) - [Malayalam](https://github.com/jwasham/coding-interview-university/issues/239) -- [Japanese (日本語)](https://github.com/jwasham/coding-interview-university/issues/257) +- [Persian - Farsi](https://github.com/jwasham/coding-interview-university/issues/186) +- [Afrikaans](https://github.com/jwasham/coding-interview-university/issues/1164) +
@@ -57,40 +64,51 @@ ![Coding at the whiteboard - from HBO's Silicon Valley](https://d3j2pkmjtin6ou.cloudfront.net/coding-at-the-whiteboard-silicon-valley.png) -یہ **نئے سافٹ ویئر انجینئرز** یا سافٹ ویئر/ویب ڈویلپمنٹ سے سافٹ ویئر انجینئرنگ میں تبدیل ہونے والوں کے لیے ہے (جہاں کمپیوٹر سائنس کا علم درکار ہے)۔ اگر آپ کے پاس کئی سالوں کا تجربہ ہے اور آپ سافٹ ویئر انجینئرنگ کے کئی سالوں کے تجربے کا دعویٰ کر رہے ہیں تو ایک مشکل انٹرویو کی توقع کریں۔ +**شرط:** +* کوڈنگ کے ساتھ تھوڑا سا تجربہ (متغیرات، لوپس، فنکشنز وغیرہ) +* صبر +* وقت -اگر آپ کے پاس سافٹ ویئر/ویب ڈویلپمنٹ کا کئی سال کا تجربہ ہے، تو نوٹ کریں کہ بڑی سافٹ ویئر کمپنیاں جیسے گوگل، ایمیزون، فیس بک اور مائیکروسافٹ سافٹ ویئر انجینئرنگ کو سافٹ ویئر/ویب ڈویلپمنٹ سے مختلف سمجھتے ہیں، اور انہیں کمپیوٹر سائنس کے علم کی ضرورت ہوتی ہے۔ +نوٹ کریں کہ یہ **سافٹ ویئر انجینئرنگ** کے لیے مطالعہ کا منصوبہ ہے، ویب ڈویلپمنٹ کے لیے نہیں۔ بڑی سافٹ ویئر کمپنیاں جیسے گوگل، ایمیزون، +فیس بک اور مائیکروسافٹ سافٹ ویئر انجینئرنگ کو ویب ڈویلپمنٹ سے مختلف سمجھتے ہیں۔ مثال کے طور پر، ایمیزون کے پاس فرنٹ اینڈ انجینئرز (FEE) اور سافٹ ویئر ڈویلپمنٹ انجینئرز (SDE)ہیں۔ یہ 2 الگ الگ کردارہیں اوران کےلیے الگ الگ انٹرویوز ہیں۔ کیونکہ ہر ایک کی اپنی ضروریات ہیں۔ ان کمپنیوں کو سافٹ ویئر ڈویلپمنٹ / انجینئرنگ کےلے کمپیوٹر سائنس کا علم درکار ہوتا ہے۔ -اگر آپ ریلائیبلٹی انجینئر یا آپریشنز انجینئر بننا چاہتے ہیں تو اختیاری فہرست (نیٹ ورکنگ، سیکیورٹی) سے مزید مطالعہ کریں۔ +یونیورسٹی کے کمپیوٹر سائنس پروگرام میں سیکھنے کے لیے بہت کچھ ہے، لیکن انٹرویو کے لیے صرف 75% جاننا ہی کافی ہے، اس لیے میں یہاں صرف اتنا ہی احاطہ کرتا ہوں۔ +مکمل خود سیکھے جانے والے سی-ایس پروگرام کے لیے، میرے اسٹڈی پلان کے وسائل کامران احمد کے کمپیوٹر سائنس روڈ میپ میں شامل کیے گئے ہیں: https://roadmap.sh/computer-science --- ## مواد کی فہرست -- [یہ کیا ہے؟](#what-is-it) -- [اسے کیوں استعمال کریں؟](#why-use-it) -- [اسے کیسے استعمال کریں](#how-to-use-it) -- [اپنے آپ کو کم نہ سمجھیں](#dont-feel-you-arent-smart-enough) -- [ویڈیو مواد کے بارے میں](#about-video-resources) -- [انٹرویو کا عمل اور عام انٹرویو کی تیاری](#interview-process--general-interview-prep) -- [انٹرویو کے لیے ایک زبان کا انتخاب کریں۔](#pick-one-language-for-the-interview) -- [کتابوں کی فہرست](#book-list) -- [شروع کرنے سے پہلے](#before-you-get-started) -- [جو آپ نہیں سیکھیں گے۔](#what-you-wont-see-covered) -- [پہلے سے ضروری علم](#prerequisite-knowledge) -- [روزانہ کی منصوبہ بندی](#the-daily-plan) -- [الگورتھمک پیچیدگی / بگ-او / اسیمپٹوٹک تجزیہ(Algorithmic complexity / Big-O / Asymptotic analysis)](#algorithmic-complexity--big-o--asymptotic-analysis) -- [ڈیٹا سٹرکچرز(Data Structures)](#data-structures) +### مطالعہ کا منصوبہ + +- [یہ کیا ہے؟](#یہ-کیا-ہے) +- [اسے کیوں استعمال کریں؟](#اسے-کیوں-استعمال-کریں) +- [اسے کیسے استعمال کریں](#اسے-کیسے-استعمال-کریں) +- [اپنے آپ کو کم نہ سمجھیں](#اپنے-آپ-کو-کم-مت-سمجھو) +- [ویڈیو مواد کے بارے میں](#ویڈیو-وسائل-کے-بارے-میں-ایک-نوٹ) +- [انٹرویو کے لیے ایک پروگرامنگ زبان کا انتخاب کریں۔](#ایک-پروگرامنگ-زبان-کا-انتخاب) +- [ڈیٹا سٹرکچرز اور الگورتھم کے لیے کتابیں](#ڈیٹا-سٹرکچرز-اور-الگورتھم-کے-لیے-کتابیں) +- [انٹرویو کی تیاری کی کتابیں](#انٹرویو-کی-تیاری-کی-کتابیں) +- [میری غلطیاں مت کرنا](#میری-غلطیاں-مت-کرنا) +- [جو آپ نہیں سیکھیں گے۔](#جو-آپ-نہیں-سیکھیں-گے) +- [روزانہ کی منصوبہ بندی](#روزانہ-کا-منصوبہ) +- [کوڈنگ سوال کی مشق](#کوڈنگ-سوال-کی-مشق) +- [کوڈنگ چیلنجز](#کوڈنگ-کے-سوالاتمسائل) + +### مطالعہ کے موضوعات + +- [الگورتھمک پیچیدگی / بگ-او / اسیمپٹوٹک تجزیہ(Algorithmic complexity / Big-O / Asymptotic analysis)](#الگورتھمک-پیچیدگی--بگ-او--اسیمپٹوٹک-تجزیہ) +- [ڈیٹا سٹرکچرز(Data Structures)](#ڈیٹا-سٹرکچرز) - [آرے (Arrays)](#arrays) - [لنکڈلسٹ (Linked Lists)](#linked-lists) - [سٹیک (Stack)](#stack) - [کیو (Queue)](#queue) - [ہیش ٹیبل (Hash table)](#hash-table) -- [مزید معلومات](#more-knowledge) +- [مزید معلومات](#مزید-معلومات) - [بینری سرچ (Binary search)](#binary-search) - [بٹ وائزاپریشنز (Bitwise operations)](#bitwise-operations) - [ٹریز (Trees)](#trees) - - [ٹریز - نوٹس اور پس منظر](#trees---notes--background) + - [ٹریز - تعارف](#trees---intro) - [بینری سرچ ٹریز (Binary search trees: BSTs)](#binary-search-trees-bsts) - [ہیپ / پریاٹری کیو / بینری ہیپ (Heap / Priority Queue / Binary Heap)](#heap--priority-queue--binary-heap) - بیلنسڈ سرچ ٹریز - عمومی جائزہ (balanced search trees - general concept, not details) @@ -107,38 +125,39 @@ - اڈجیسنسی میٹرکس (adjacency matrix) - اڈجیسنسی لسٹ (adjacency list) - ٹریورسل (traversals: BFS, DFS) -- [اس سے بھی زیادہ معلومات](#even-more-knowledge) +- [اس سے بھی زیادہ معلومات](#اس-سے-بھی-زیادہ-معلومات) - [رکرین / تکرار (Recursion)](#recursion) - [ڈینیمک پروگرامنگ](#dynamic-programming) - - [ابجیکٹ پروگرامنگ](#object-oriented-programming) - [ڈیزائن پیٹرن](#design-patterns) - [امتزاج (n منتخب k) اور امکان](#combinatorics-n-choose-k--probability) - [تخمینہ الگورتھم ،NPاورNP-مکمل (NP, NP-Complete and Approximation Algorithms)](#np-np-complete-and-approximation-algorithms) + - [How computers process a program](#how-computers-process-a-program) - [کیچز](#caches) - [پروسسزاور تھریڈز](#processes-and-threads) - [ٹیسٹنگ](#testing) - - [شیڈولنگ](#scheduling) - [سٹرنگ تلاش کرنا اور تبدیل کرنا](#string-searching--manipulations) - [ٹرایز (Tries)](#tries) - [اعشاریہ کے ساتھ نمبر](#floating-point-numbers) - [یونیکوڈ](#unicode) - [اینڈیاننس](#endianness) - [نیٹ ورکنگ](#networking) -- [سسٹم ڈیزائن، اسکیل ایبلٹی، ڈیٹا ہینڈلنگ](#system-design-scalability-data-handling) (اگر آپ کو 4 سال سے زیادہ کا تجربہ ہے۔) -- [حتمی جائزہ](#final-review) -- [کوڈنگ سوال کی مشق](#coding-question-practice) -- [کوڈنگ کی مشقیں/چیلنجز](#coding-exerciseschallenges) -- [ایک بار جب آپ انٹرویو کے قریب پہنچ جائیں۔](#once-youre-closer-to-the-interview) -- [آپ کا رزیومے](#your-resume) -- [اپنے انٹرویو لینے والے کی طرح سوچیں۔](#be-thinking-of-for-when-the-interview-comes) -- [انٹرویو لینے والے کے لیے سوالات](#have-questions-for-the-interviewer) -- [ایک بار جب آپ کو نوکری مل جائے گی۔](#once-youve-got-the-job) +- [حتمی جائزہ](#حتمی-جائزہ) + +### ملازمت حاصل کرنا + +- [اپنا ریزومےاپ ڈیٹ کریں](#اپنے-ریزیومے-کو-اپ-ڈیٹ-کریں) +- [نوکری تلاش کریں](#find-a-job) +- [انٹرویو کا عمل اور عام انٹرویو کی تیاری](#انٹرویو-کا-عمل-اور-عام-انٹرویو-کی-تیاری) +- [اپنے انٹرویو لینے والے کی طرح سوچیں۔](#اپنے-انٹرویو-لینے-والے-کی-طرح-سوچیں) +- [انٹرویو لینے والے کے لیے سوالات](#انٹرویو-لینے-والے-کے-لیے-سوالات) +- [ایک بار جب آپ کو نوکری مل جائے گی۔](#ایک-بار-جب-آپ-کو-نوکری-مل-جائے-گی) ---------------- ذیل کی چیزیں اختیاری ہیں ---------------- -## اضافی مواد +## اختیاری اضافی عنوانات اور مواد - [اضافی کتابیں](#additional-books) +- [سسٹم ڈیزائن، اسکیل ایبلٹی، ڈیٹا ہینڈلنگ](#system-design-scalability-data-handling) (اگر آپ کو 4 سال سے زیادہ کا تجربہ ہے۔) - [اضافی معلومات](#additional-learning) - [کمپائلر](#compilers) - [ایماکس اور vi(m)](#emacs-and-vim) @@ -176,7 +195,6 @@ - [لینیرپروگرامنگ](#linear-programming-videos) - [جیومیٹری، کنویکس ہل](#geometry-convex-hull-videos) - [مجرد ریاضی](#discrete-math) - - [مشین لرننگ](#machine-learning) - [کچھ مضامین پر اضافی تفصیل](#additional-detail-on-some-subjects) - [ویڈیو سیریز](#video-series) - [کمپیوٹر سائنس کورسز](#computer-science-courses) @@ -184,327 +202,377 @@ --- -## Why use it? +## اسے کیوں استعمال کریں؟ -When I started this project, I didn't know a stack from a heap, didn't know Big-O anything, anything about trees, or how to -traverse a graph. If I had to code a sorting algorithm, I can tell ya it wouldn't have been very good. -Every data structure I've ever used was built into the language, and I didn't know how they worked -under the hood at all. I've never had to manage memory unless a process I was running would give an "out of -memory" error, and then I'd have to find a workaround. I've used a few multidimensional arrays in my life and -thousands of associative arrays, but I've never created data structures from scratch. +اگر آپ کسی بڑی کمپنی میں سافٹ ویئر انجینئر کے طور پر کام کرنا چاہتے ہیں تو یہ وہ چیزیں ہیں جو آپ کو جاننا ہوں گی۔ -It's a long plan. It may take you months. If you are familiar with a lot of this already it will take you a lot less time. +اگر آپ میری طرح کمپیوٹر سائنس میں ڈگری حاصل کرنے سے محروم رہ گئے تو اس سے آپ کی زندگی کے چار سال بچ جائیں گے۔ -## How to use it +جب میں نے یہ پروجیکٹ شروع کیا تھا، مجھےہیپ ، بگ-O یا ٹریز جیسا کچھ معلوم نہیں تھا،نہ ہی یہ معلوم تھا کہ گراف کے ساتھ کام کیسے کرتےہیں. اگر مجھے سورٹنگ الگورتھم کو کوڈ کرنا ہوتا تو میں آپ کو بتا سکتا ہوں کہ یہ میے لیے بہت مشکل کام تھا۔ +ہر ڈیٹا سٹرکچر جو میں نے کبھی استعمال کیا تھا مجھے نہیں معلوم تھا کہ وہ کیسے کام کرتاہے۔ مجھے کبھی بھی میموری کو سنبھالنے کی ضرورت نہیں تھی جب تک کہ میں جس پروسس کو چلا رہا ہوں اسے "میموری آؤٹ" کا ایرر نہیں ملتا تھا۔ میں نے اپنی زندگی میں چند کثیر جہتی اریزاورہزاروں ایسوسی ایٹیو ارےکا استعمال کیا، لیکن میں نے کبھی بھی شروع سے ڈیٹا سٹرکچرز نہیں بنائے۔ -Everything below is an outline, and you should tackle the items in order from top to bottom. +یہ ایک طویل منصوبہ ہے۔ اس میں آپ کو مہینے لگ سکتے ہیں۔ اگر آپ پہلے ہی اس میں سے بہت کچھ سے واقف ہیں تو اس میں آپ کو بہت کم وقت لگے گا۔ -I'm using Github's special markdown flavor, including tasks lists to check progress. +## اسے کیسے استعمال کریں -**Create a new branch so you can check items like this, just put an x in the brackets: [x]** +نیچے دی گئی ہر چیز ایک خاکہ ہے، اور آپ کو اشیاء کو اوپر سے نیچے تک ترتیب سے نمٹنا چاہیے۔ +میں GitHub کا خصوصی مارک ڈاؤن ورژن استعمال کر رہا ہوں، جس میں پیش رفت کو ٹریک کرنے کے لیے ٹاسک کی فہرست شامل ہے۔ + - [GitHub-flavored markdown کے بارے میں مزید](https://guides.github.com/features/mastering-markdown/#GitHub-flavored-markdown) - Fork a branch and follow the commands below +### اگر آپ گٹ استعمال نہیں کرنا چاہتے -`git checkout -b progress` +اس صفحہ پر، اوپر کے قریب کوڈ(Code) بٹن پر کلک کریں، پھر "زپ ڈاؤن لوڈ کریں(Download Zip)" پر کلک کریں۔ فائل کو ان زپ کریں اور آپ ٹیکسٹ فائلوں کے ساتھ کام کر سکتے ہیں۔ -`git remote add jwasham https://github.com/jwasham/coding-interview-university` +اگر آپ ایک کوڈ ایڈیٹر میں کھول رہے ہیں جو مارک ڈاؤن کو سمجھتا ہے، تو آپ کو ہر چیز اچھی طرح سے فارمیٹ کی ہوئی نظر آئے گی۔ -`git fetch --all` +![ریپو کو زپ فائل کے طور پر کیسے ڈاؤن لوڈ کریں۔](https://d3j2pkmjtin6ou.cloudfront.net/how-to-download-as-zip.png) - Mark all boxes with X after you completed your changes +### اگر آپ گٹ کے ساتھ کام کر سکتے ہیں -`git add .` +ایک نئی برانچ بنائیں تاکہ آپ اس طرح کے آئٹمز کو چیک کر سکیں، صرف بریکٹ میں ایک x لگائیں: [x] -`git commit -m "Marked x"` + ۱. ***گٹ ہب (GitHub) ریپو*** `https://github.com/jwasham/coding-interview-university` کوفورک بٹن پر کلک کرکے فورک کریں۔ -`git rebase jwasham/master` + ![GitHub ریپو کو فورک کریں:](https://d3j2pkmjtin6ou.cloudfront.net/fork-button.png) -`git push --force` +۲. اپنی لوکل ریپو پر کلون کریں: -[More about Github-flavored markdown](https://guides.github.com/features/mastering-markdown/#GitHub-flavored-markdown) + ``` + git clone git@github.com:/coding-interview-university.git + cd coding-interview-university + git checkout -b progress + git remote add jwasham https://github.com/jwasham/coding-interview-university + git fetch --all + ``` +۳. اپنی تبدیلیاں مکمل کرنے کے بعد تمام خانوں کو X کے ساتھ نشان زد کریں: -## Don't feel you aren't smart enough + ``` + git add . + git commit -m "Marked x" + git rebase jwasham/main + git push --set-upstream origin progress + git push --force + ``` -- Successful software engineers are smart, but many have an insecurity that they aren't smart enough. -- [The myth of the Genius Programmer](https://www.youtube.com/watch?v=0SARbwvhupQ) -- [It's Dangerous to Go Alone: Battling the Invisible Monsters in Tech](https://www.youtube.com/watch?v=1i8ylq4j_EY) +## اپنے آپ کو کم مت سمجھو -## About Video Resources +- کامیاب سافٹ ویئر انجینئرز ہوشیار ہوتے ہیں، لیکن بہت سے لوگوں کو یہ عدم تحفظ ہوتا ہے کہ وہ اتنے ہوشیار نہیں ہیں۔ +- مندرجہ ذیل ویڈیوز آپ کو اس عدم تحفظ پر قابو پانے میں مدد کر سکتی ہیں: + - [The myth of the Genius Programmer](https://www.youtube.com/watch?v=0SARbwvhupQ) + - [It's Dangerous to Go Alone: Battling the Invisible Monsters in Tech](https://www.youtube.com/watch?v=1i8ylq4j_EY) -Some videos are available only by enrolling in a Coursera or EdX class. These are called MOOCs. -Sometimes the classes are not in session so you have to wait a couple of months, so you have no access. +## ویڈیو وسائل کے بارے میں ایک نوٹ - I'd appreciate your help to add free and always-available public sources, such as YouTube videos to accompany the online course videos. - I like using university lectures. +کچھ ویڈیوز صرف Coursera یا EdX کلاس میں داخلہ لے کر دستیاب ہیں۔ یہ MOOCs کہلاتے ہیں۔ +بعض اوقات کلاسز سیشن میں نہیں ہوتیں اس لیے آپ کو چند ماہ انتظار کرنا پڑتا ہے، اس لیے آپ کو رسائی نہیں ہوتی۔ +آن لائن کورس کے وسائل کو مفت اور ہمیشہ دستیاب عوامی ذرائع سے تبدیل کرنا بہت اچھا ہوگا، جیسے یوٹیوب ویڈیوز (ترجیحی طور پر یونیورسٹی کے لیکچرز)، تاکہ آپ لوگ کسی بھی وقت ان کا مطالعہ کر سکیں، بجاے کہ صرف اس وقت کے جب ایک مخصوص آن لائن کورس سیشن میں ہو۔ -## Interview Process & General Interview Prep +## ایک پروگرامنگ زبان کا انتخاب -- [ ] [ABC: Always Be Coding](https://medium.com/always-be-coding/abc-always-be-coding-d5f8051afce2#.4heg8zvm4) -- [ ] [Whiteboarding](https://medium.com/@dpup/whiteboarding-4df873dbba2e#.hf6jn45g1) -- [ ] [Demystifying Tech Recruiting](https://www.youtube.com/watch?v=N233T0epWTs) -- [ ] How to Get a Job at the Big 4: - - [ ] [How to Get a Job at the Big 4 - Amazon, Facebook, Google & Microsoft (video)](https://www.youtube.com/watch?v=YJZCUhxNCv8) -- [ ] Cracking The Coding Interview Set 1: - - [ ] [Gayle L McDowell - Cracking The Coding Interview (video)](https://www.youtube.com/watch?v=rEJzOhC5ZtQ) - - [ ] [Cracking the Coding Interview with Author Gayle Laakmann McDowell (video)](https://www.youtube.com/watch?v=aClxtDcdpsQ) -- [ ] Cracking the Facebook Coding Interview - - [ ] [The Approach](https://www.youtube.com/watch?v=wCl9kvQGHPI) - - [ ] [Problem Walkthrough](https://www.youtube.com/watch?v=4UWDyJq8jZg) -- [ ] Prep Course: - - [ ] [Software Engineer Interview Unleashed (paid course)](https://www.udemy.com/software-engineer-interview-unleashed): - - Learn how to make yourself ready for software engineer interviews from a former Google interviewer. - - [ ] [Python for Data Structures, Algorithms, and Interviews (paid course)](https://www.udemy.com/python-for-data-structures-algorithms-and-interviews/): - - A Python centric interview prep course which covers data structures, algorithms, mock interviews and much more. - - [ ] [Intro to Data Structures and Algorithms using Python (Udacity free course)](https://www.udacity.com/course/data-structures-and-algorithms-in-python--ud513): - - A free Python centric data structures and algorithms course. - - [ ] [Data Structures and Algorithms Nanodegree! (Udacity paid Nanodegree)](https://www.udacity.com/course/data-structures-and-algorithms-nanodegree--nd256): - - Get hands-on practice with over 100 data structures and algorithm exercises and guidance from a dedicated mentor to help prepare you for interviews and on-the-job scenarios. +آپ جو کوڈنگ انٹرویوز کرتے ہیں اس کے لیے آپ کو پروگرامنگ لینگویج کا انتخاب کرنا ہوگا، +لیکن آپ کو ایک ایسی زبان بھی تلاش کرنے کی ضرورت ہوگی جسے آپ کمپیوٹر سائنس کے تصورات کا مطالعہ کرنے کے لیے استعمال کر سکیں۔ -## Pick One Language for the Interview +ترجیحی طور پر زبان ایک ہی ہونی چاہیے، تانکہ آپ کو صرف ایک میں مہارت حاصل کرنے کی ضرورت ہو۔ -You can use a language you are comfortable in to do the coding part of the interview, but for large companies, these are solid choices: +### اس اسٹڈی پلان کے لیے -- C++ -- Java -- Python +جب میں نے مطالعہ کا منصوبہ بنایا تو میں نے اس کے لیے 2 زبانیں استعمال کیں: C اور Python -You could also use these, but read around first. There may be caveats: +* سی (C): نچلی سطح کی زبان۔ آپ کو پوائنٹرز اور میموری ایلوکیشن/ڈی ایلوکیشن سے نمٹنے کی اجازت دیتا ہے، تاکہ آپ اپنی خون میں ڈیٹا سٹرکچر اور الگورتھم کو محسوس کریں۔ پائتھون یا جاوا جیسی اعلیٰ سطح کی زبانوں میں، یہ آپ سے پوشیدہ ہیں۔ روزمرہ کے کام میں، یہ بہت اچھا ہے، لیکن جب آپ یہ سیکھ رہے ہیں کہ یہ نچلے درجے کے ڈیٹا سٹرکچر کیسے بنائے جاتے ہیں، تو جڑ کے قریب محسوس کرنا بہت اچھا ہے۔ + - سی ہر جگہ ہے۔ جب آپ مطالعہ کر رہے ہوں گے تو آپ کو کتابوں، لیکچرز، ویڈیوز، *ہر جگہ* میں مثالیں نظر آئیں گی۔ + - [سی پروگرامنگ لینگویج، دوسرا ایڈیشن (The C Programming Language, 2nd Edition)](https://www.amazon.com/Programming-Language-Brian-W-Kernighan/dp/0131103628) + - یہ ایک مختصر کتاب ہے، لیکن یہ آپ کو C زبان پر بہت اچھا کنٹرول دے گی اور اگر آپ اس پر تھوڑی سی مشق کریں گے تو آپ جلد مہارت حاصل کر لیں گے۔ C کو سمجھنا آپ کو یہ سمجھنے میں مدد کرتا ہے کہ پروگرام اور میموری کیسے کام کرتے ہیں۔ + - آپ کو کتاب کی بہت گہرائی میں جانے کی ضرورت نہیں ہے (نہ ہی اسے ختم کرنے کی)۔ بس اتنی مہارت حاصل کر لیں کے آپ کو C میں پڑھنے اور لکھنے میں آسانی ہو۔ + - [کتاب میں موجود سوالات کے جوابات](https://github.com/lekkas/c-algorithms) +* پائتھون(Python): جدید اور اظہار کرنے میں بہت آسان، میں نے یہ سیکھی کیونکہ یہ بہت مفید ہے اور مجھے انٹرویو میں کم کوڈ لکھنے میں مدد دیتی ہے۔ -- JavaScript -- Ruby +یہ میری ترجیح ہے۔ تم وہی کرو جو تمہیں پسند ہو۔ -Here is an article I wrote about choosing a language for the interview: [Pick One Language for the Coding Interview](https://startupnextdoor.com/important-pick-one-language-for-the-coding-interview/) +ہو سکتا ہے آپ کو اس کی ضرورت نہ ہو، لیکن نئی زبان سیکھنے کے لیے یہاں کچھ سائٹیں ہیں: +- [Exercism](https://exercism.org/tracks) +- [Codewars](http://www.codewars.com) +- [HackerEarth](https://www.hackerearth.com/for-developers/) +- [Scaler Topics (Java, C++)](https://www.scaler.com/topics/) -You need to be very comfortable in the language and be knowledgeable. +### آپ کے کوڈنگ انٹرویو کے لیے -Read more about choices: -- http://www.byte-by-byte.com/choose-the-right-language-for-your-coding-interview/ -- http://blog.codingforinterviews.com/best-programming-language-jobs/ +آپ انٹرویو کا کوڈنگ حصہ کرنے کے لیے ایسی زبان استعمال کر سکتے ہیں جس میں آپ کو آسانی ہو، لیکن بڑی کمپنیوں کے لیے یہ بہترین انتخاب ہیں: -[See language resources here](programming-language-resources.md) +- سی++ (C++) +- جاوا (Java) +- پائتھون (Python) -You'll see some C, C++, and Python learning included below, because I'm learning. There are a few books involved, see the bottom. +آپ مندرجہ ذیل کو بھی استعمال کرسکتے ہیں لیکن پہلے پڑھ سکتے ہیں۔ انتباہات ہو سکتے ہیں: -## Book List +- جاوا اسکرپٹ (JavaScript) +- روبی (Ruby) -This is a shorter list than what I used. This is abbreviated to save you time. +یہاں ایک مضمون ہے جو میں نے انٹرویو کے لیے زبان کے انتخاب کے بارے میں لکھا تھا: +[کوڈنگ انٹرویو کے لیے ایک زبان چنیں](https://startupnextdoor.com/important-pick-one-language-for-the-coding-interview/). +یہ اصل مضمون ہے جس پر میری پوسٹ مبنی تھی: [انٹرویوز کے لیے پروگرامنگ لینگویج کا انتخاب](https://web.archive.org/web/20210516054124/http://blog.codingforinterviews.com/best-programming-language-jobs/) -### Interview Prep +آپ کو زبان میں بہت مہارت اور علم رکھنے کی ضرورت ہے۔ -- [ ] [Programming Interviews Exposed: Coding Your Way Through the Interview, 4th Edition](https://www.amazon.com/Programming-Interviews-Exposed-Through-Interview/dp/111941847X/) - - answers in C++ and Java - - this is a good warm-up for Cracking the Coding Interview - - not too difficult, most problems may be easier than what you'll see in an interview (from what I've read) -- [ ] [Cracking the Coding Interview, 6th Edition](http://www.amazon.com/Cracking-Coding-Interview-6th-Programming/dp/0984782850/) - - answers in Java +انتخاب کے بارے میں مزید پڑھیں: +- [اپنے کوڈنگ انٹرویو کے لیے صحیح زبان کا انتخاب کریں](http://www.byte-by-byte.com/choose-the-right-language-for-your-coding-interview/) -### If you have tons of extra time: +[زبان سے متعلق وسائل یہاں دیکھیں](programming-language-resources.md) -Choose one: +## ڈیٹا سٹرکچرز اور الگورتھم کے لیے کتابیں -- [ ] [Elements of Programming Interviews (C++ version)](https://www.amazon.com/Elements-Programming-Interviews-Insiders-Guide/dp/1479274836) -- [ ] [Elements of Programming Interviews in Python](https://www.amazon.com/Elements-Programming-Interviews-Python-Insiders/dp/1537713949/) -- [ ] Elements of Programming Interviews (Java version) - - [book](https://www.amazon.com/Elements-Programming-Interviews-Java-Insiders/dp/1517435803/) - - [Companion Project - Method Stub and Test Cases for Every Problem in the Book](https://github.com/gardncl/elements-of-programming-interviews) +یہ کتاب کمپیوٹر سائنس کے لیے آپ کی بنیاد بنائے گی۔ -### Language Specific +صرف ایک کا انتخاب کریں، ایسی زبان میں جس میں آپ کو مہارت حاصل ہو۔ آپ کو بہت زیادہ پڑھنا اور کوڈنگ کرنا ہوگی۔ -**You need to choose a language for the interview (see above).** +### سی (C) -Here are my recommendations by language. I don't have resources for all languages. I welcome additions. +- [سی میں الگورتھم، حصے 1-5 (بنڈل)، تیسرا ایڈیشن](https://www.amazon.com/Algorithms-Parts-1-5-Bundle-Fundamentals/dp/0201756080) + - بنیادی باتیں، ڈیٹا سٹرکچر، سارٹنگ، تلاش کرنا، اور گراف الگورتھم -If you read through one of these, you should have all the data structures and algorithms knowledge you'll need to start doing coding problems. -**You can skip all the video lectures in this project**, unless you'd like a review. +### پا ئیتھون (Python) -[Additional language-specific resources here.](programming-language-resources.md) +- [پا ئیتھون میں ڈیٹا کے سٹرکچر اور الگورتھم](https://www.amazon.com/Structures-Algorithms-Python-Michael-Goodrich/dp/1118290275/) + - مصنف Goodrich, Tamassia, Goldwasser + - مجھے یہ کتاب پسند ہے۔ اس نے ہر چیز کا احاطہ کیا ہے۔ + - پائتھون کے کوڈ + - میری چمکتی ہوئی کتاب کی رپورٹ: https://startupnextdoor.com/book-report-data-structures-and-algorithms-in-python/ -### C++ +### جاوا (Java) -I haven't read these two, but they are highly rated and written by Sedgewick. He's awesome. +تمھارا انتخاب: -- [ ] [Algorithms in C++, Parts 1-4: Fundamentals, Data Structure, Sorting, Searching](https://www.amazon.com/Algorithms-Parts-1-4-Fundamentals-Structure/dp/0201350882/) -- [ ] [Algorithms in C++ Part 5: Graph Algorithms](https://www.amazon.com/Algorithms-Part-Graph-3rd-Pt-5/dp/0201361183/) - -If you have a better recommendation for C++, please let me know. Looking for a comprehensive resource. - -### Java - -- [ ] [Algorithms (Sedgewick and Wayne)](https://www.amazon.com/Algorithms-4th-Robert-Sedgewick/dp/032157351X/) - - videos with book content (and Sedgewick!) on coursera: +- Goodrich, Tamassia, Goldwasser + - [Data Structures and Algorithms in Java](https://www.amazon.com/Data-Structures-Algorithms-Michael-Goodrich/dp/1118771338/) +- Sedgewick and Wayne: + - [Algorithms](https://www.amazon.com/Algorithms-4th-Robert-Sedgewick/dp/032157351X/) + - مفت کورسیرا کورس جو کتاب کا احاطہ کرتا ہے (مصنفین کے ذریعہ پڑھایا گیا): - [Algorithms I](https://www.coursera.org/learn/algorithms-part1) - [Algorithms II](https://www.coursera.org/learn/algorithms-part2) -OR: +### سی++ (++C) -- [ ] [Data Structures and Algorithms in Java](https://www.amazon.com/Data-Structures-Algorithms-Michael-Goodrich/dp/1118771338/) - - by Goodrich, Tamassia, Goldwasser - - used as optional text for CS intro course at UC Berkeley - - see my book report on the Python version below. This book covers the same topics. +تمھارا انتخاب:: -### Python +- Goodrich, Tamassia, and Mount + - [Data Structures and Algorithms in C++, 2nd Edition](https://www.amazon.com/Data-Structures-Algorithms-Michael-Goodrich/dp/0470383275) +- Sedgewick and Wayne + - [Algorithms in C++, Parts 1-4: Fundamentals, Data Structure, Sorting, Searching](https://www.amazon.com/Algorithms-Parts-1-4-Fundamentals-Structure/dp/0201350882/) + - [Algorithms in C++ Part 5: Graph Algorithms](https://www.amazon.com/Algorithms-Part-Graph-3rd-Pt-5/dp/0201361183/) -- [ ] [Data Structures and Algorithms in Python](https://www.amazon.com/Structures-Algorithms-Python-Michael-Goodrich/dp/1118290275/) - - by Goodrich, Tamassia, Goldwasser - - I loved this book. It covered everything and more. - - Pythonic code - - my glowing book report: https://startupnextdoor.com/book-report-data-structures-and-algorithms-in-python/ +## انٹرویو کی تیاری کی کتابیں +آپ کو ان میں سے بہت زیادہ خریدنے کی ضرورت نہیں ہے۔ ایمانداری سے "کریکنگ دی کوڈنگ انٹرویو(Cracking the Coding Interview)" شاید کافی ہے، +لیکن میں نے خود کو مزید مشق دینے کے لیے بہت کچھ خریدا۔ لیکن میں ہمیشہ بہت زیادہ کرتا ہوں۔ -## Before you Get Started +میں نے یہ دونوں خریدے ہیں۔ انہوں نے مجھے کافی مشق دی۔ -This list grew over many months, and yes, it kind of got out of hand. +- [پروگرامنگ انٹرویوز کا انکشاف: انٹرویو کے ذریعے اپنے راستے کی کوڈنگ، 4th ایڈیشن](https://www.amazon.com/Programming-Interviews-Exposed-Through-Interview/dp/111941847X/) + - سی++ (++C) اور جاوا (Java) میں جوابات + - کوڈنگ انٹرویو کو کریک کرنے کے لیے یہ ایک اچھی شروعات ہے۔ + - زیادہ مشکل نہیں۔ زیادہ تر مسائل اس سے آسان ہوسکتے ہیں جو آپ انٹرویو میں دیکھیں گے (اس سے جو میں نے پڑھا ہے) +- [کریکنگ دی کوڈنگ انٹرویو، چھٹا ایڈیشن](http://www.amazon.com/Cracking-Coding-Interview-6th-Programming/dp/0984782850/) + - جاوا میں جوابات -Here are some mistakes I made so you'll have a better experience. +### اگر آپ کے پاس بہت زیادہ وقت ہے: -### 1. You Won't Remember it All +ایک کا انتخاب کرو: -I watched hours of videos and took copious notes, and months later there was much I didn't remember. I spent 3 days going -through my notes and making flashcards so I could review. +- [پروگرامنگ انٹرویوز کے عناصر (C++ ورژن)](https://www.amazon.com/Elements-Programming-Interviews-Insiders-Guide/dp/1479274836) +- [پا ئیتھون میں پروگرامنگ انٹرویوز کے عناصر](https://www.amazon.com/Elements-Programming-Interviews-Python-Insiders/dp/1537713949/) +- [پروگرامنگ انٹرویوز کے عناصر (جاوا ورژن)](https://www.amazon.com/Elements-Programming-Interviews-Java-Insiders/dp/1517435803/) + - [ساتھی پروجیکٹ - کتاب میں ہر مسئلے کے لیے ٹیسٹ کیسز](https://github.com/gardncl/elements-of-programming-interviews) -Read please so you won't make my mistakes: +## میری غلطیاں مت کرنا -[Retaining Computer Science Knowledge](https://startupnextdoor.com/retaining-computer-science-knowledge/). +یہ فہرست کئی مہینوں میں بڑھی، اور ہاں، یہ ہاتھ سے نکل گئی۔ -A course recommended to me (haven't taken it): [Learning how to Learn](https://www.coursera.org/learn/learning-how-to-learn) +یہ کچھ غلطیاں ہیں جو میں نے کی تھی۔ تو آپ کو ایک بہتر تجربہ ملے گا۔ اور آپ مہینوں کا وقت بچائیں گے۔ -### 2. Use Flashcards +### 1. آپ سب یادنہیں رکھ سکیں گے -To solve the problem, I made a little flashcards site where I could add flashcards of 2 types: general and code. -Each card has different formatting. +میں نے گھنٹوں کی ویڈیوز دیکھی اور کافی نوٹ لیے، اور مہینوں بعد مجھے بہت کچھ یاد نہیں تھا۔ میں نے 3 دن گزارے، اپنے نوٹس پڑھے اور فلیش کارڈز بنائے، تاکہ میں جائزہ لے سکوں۔ مجھے اس سارے علم کی ضرورت نہیں تھی۔ -I made a mobile-first website so I could review on my phone and tablet, wherever I am. +براہ کرم، پڑھیں تاکہ آپ میری غلطی نہ کریں: -Make your own for free: +[کمپیوٹر سائنس کا علم برقرار رکھنا](https://startupnextdoor.com/retaining-computer-science-knowledge/). -- [Flashcards site repo](https://github.com/jwasham/computer-science-flash-cards) -- [My flash cards database (old - 1200 cards)](https://github.com/jwasham/computer-science-flash-cards/blob/master/cards-jwasham.db): -- [My flash cards database (new - 1800 cards)](https://github.com/jwasham/computer-science-flash-cards/blob/master/cards-jwasham-extreme.db): +### 2. فلیش کارڈز استعمال کریں -Keep in mind I went overboard and have cards covering everything from assembly language and Python trivia to machine learning and statistics. It's way too much for what's required. +اس مسئلے کو حل کرنے کے لیے، میں نے ایک چھوٹی سی فلیش کارڈز سائٹ بنائی جہاں میں 2 اقسام کے فلیش کارڈز شامل کر سکتا ہوں: جنرل اور کوڈ۔ +ہر کارڈ کی فارمیٹنگ مختلف ہوتی ہے۔ میں نے ایک موبائل مسابقتی ویب سائٹ بنائی ہے، تاکہ میں اپنے فون یا ٹیبلیٹ پر جہاں بھی ہوں، جائزہ لے سکوں۔ -**Note on flashcards:** The first time you recognize you know the answer, don't mark it as known. You have to see the -same card and answer it several times correctly before you really know it. Repetition will put that knowledge deeper in -your brain. +اپنےلیے مفت میں بنائیں: -An alternative to using my flashcard site is [Anki](http://ankisrs.net/), which has been recommended to me numerous times. It uses a repetition system to help you remember. -It's user-friendly, available on all platforms and has a cloud sync system. It costs $25 on iOS but is free on other platforms. +- [فلیش کارڈز سائٹ ریپو](https://github.com/jwasham/computer-science-flash-cards) -My flashcard database in Anki format: https://ankiweb.net/shared/info/25173560 (thanks [@xiewenya](https://github.com/xiewenya)) +**میں اپنے فلیش کارڈز استعمال کرنے کا مشورہ نہیں دیتا۔** یہ بہت زیادہ ہیں اور ان میں سے زیادہ تر چیزیں ایسی ہیں جن کی آپ کو ضرورت نہیں ہے۔ -### 3. Start doing coding interview questions while you're learning data structures and algorithms, +لیکن اگر آپ میری بات نہیں سننا چاہتے، تو آپ یہاں جائیں: +- [میرے فلیش کارڈز کا ڈیٹا بیس (1200 کارڈز)](https://github.com/jwasham/computer-science-flash-cards/blob/main/cards-jwasham.db): +- [میرے فلیش کارڈز کا ڈیٹا بیس (انتہائی - 1800 کارڈز)](https://github.com/jwasham/computer-science-flash-cards/blob/main/cards-jwasham-extreme.db): -You need to apply what you're learning to solving problems, or you'll forget. I made this mistake. Once you've learned a topic, -and feel comfortable with it, like linked lists, open one of the coding interview books and do a couple of questions regarding -linked lists. Then move on to the next learning topic. Then later, go back and do another linked list problem, -or recursion problem, or whatever. But keep doing problems while you're learning. You're not being hired for knowledge, -but how you apply the knowledge. There are several books and sites I recommend. -See here for more: [Coding Question Practice](#coding-question-practice) +ذہن میں رکھیں کہ میں اوور بورڈ گیا اور میرے جو کارڈز ہیں ان میں اسمبلی لینگویج اور پائیتھون کی چھوٹی معلومات سے لے کر مشین لرننگ اور اعدادوشمار تک ہر چیز کا احاطہ کیا گیا ہے۔ +جو کے ضرورت سے بہت زیادہ ہے۔ -### 4. Review, review, review +**فلیش کارڈز پر نوٹ:** پہلی بار جب آپ پہچانیں گے کہ آپ کو جواب معلوم ہے تو اسے معلوم کے طور پر نشان زد نہ کریں۔ایک ہی کارڈ دیکھیں + اور اس کا کئی بار صحیح جواب دیں اس سے پہلے کہ آپ واقعی اسے نشان زدہ کریں۔ تکرار اس علم کو آپ کا دماغ کی مزید گہرائی میں اتار دے گی۔ -I keep a set of cheat sheets on ASCII, OSI stack, Big-O notations, and more. I study them when I have some spare time. +میری فلیش کارڈ سائٹ کو استعمال کرنے کا ایک متبادل ہے [Anki](http://ankisrs.net/)، جو مجھے متعدد بار تجویز کیا گیا ہے۔ +یہ آپ کو یاد رکھنے میں مدد کے لیے تکرار کا نظام استعمال کرتا ہے۔ یہ صارف دوست ہے، تمام پلیٹ فارمز پر دستیاب ہے اور اس میں کلاؤڈ سنک سسٹم ہے۔ +ای-اہ-ایس (iOS) پر اس کی قیمت $25 ہے لیکن دوسرے پلیٹ فارمز پر مفت ہے۔ -Take a break from programming problems for a half hour and go through your flashcards. +انکی (Anki)فارمیٹ میں میرا فلیش کارڈ ڈیٹا بیس: https://ankiweb.net/shared/info/25173560 (شکریہ [@xiewenya](https://github.com/xiewenya)). -### 5. Focus +کچھ طلباء نے سفید جگہ کے ساتھ فارمیٹنگ کے مسائل کا ذکر کیا ہے جنہیں درج ذیل کام کرکے حل کیا جا سکتا ہے: ڈیک کھولیں، کارڈ میں ترمیم کریں، کارڈز پر کلک کریں، "اسٹائلنگ" ریڈیو بٹن کو منتخب کریں، کارڈ کی کلاس میں ";white-space: pre" ممبر کو شامل کریں۔ -There are a lot of distractions that can take up valuable time. Focus and concentration are hard. Turn on some music -without lyrics and you'll be able to focus pretty well. +### 3. جب آپ سیکھ رہے ہوں تو کوڈنگ انٹرویو کے سوالات کریں -## What you won't see covered +یہ بہت اہم ہے. -These are prevalent technologies but not part of this study plan: +جب آپ ڈیٹا سٹرکچر اور الگورتھم سیکھ رہے ہوں تو انٹرویو کے سوالات کو کوڈنگ کرنا شروع کریں۔ -- SQL -- Javascript -- HTML, CSS, and other front-end technologies +آپ جو سیکھ رہے ہیں اسے مسائل کو حل کرنے کے لیے لاگو کرنے کی ضرورت ہے، ورنہ آپ بھول جائیں گے۔ میں نے یہ غلطی کی۔ -## The Daily Plan +ایک بار جب آپ نے کوئی موضوع سیکھ لیا، اور اس میں کسی حد تک مہارت محسوس کریں، مثال کے طور پر، **لنکڈلسٹ**: +1. ان میں سے ایک کھولیں [کوڈنگ انٹرویو کی کتابیں](#interview-prep-books) (یا مندرجہ ذیل کوڈنگ سوالات ویب سائٹس) +2. لنکڈلسٹ سے متعلق 2 یا 3 سوالات کریں۔ +3. اگلے موضوع کی طرف بڑھیں۔ +4. بعد میں، واپس جائیں اور لنکڈ لسٹ کے مزید 2 یا 3 سوالات کریں۔ +5. یہ ہر نئے موضوع کے ساتھ کریں جو آپ سیکھتے ہیں۔ -Some subjects take one day, and some will take multiple days. Some are just learning with nothing to implement. +**جب آپ یہ سب چیزیں سیکھ رہے ہوں تو سوالات کرتے رہیں، اس کے بعد نہیں۔** -Each day I take one subject from the list below, watch videos about that subject, and write an implementation in: -- C - using structs and functions that take a struct * and something else as args. -- C++ - without using built-in types -- C++ - using built-in types, like STL's std::list for a linked list -- Python - using built-in types (to keep practicing Python) -- and write tests to ensure I'm doing it right, sometimes just using simple assert() statements -- You may do Java or something else, this is just my thing. +آپ کو علم کی وجہ سے نوکری پر نہیں رکھا جا رہا ہے، بلکہ آپ کو اس لیے رکھا گیا ہے کہ آپ علم کو کیسے استعمال کرتے ہیں۔ -You don't need all these. You need only [one language for the interview](#pick-one-language-for-the-interview). +ذیل میں اس کے لیے بہت سے وسائل موجود ہیں۔ کام جاری رکھیں۔ -Why code in all of these? -- Practice, practice, practice, until I'm sick of it, and can do it with no problem (some have many edge cases and bookkeeping details to remember) -- Work within the raw constraints (allocating/freeing memory without help of garbage collection (except Python or Java)) -- Make use of built-in types so I have experience using the built-in tools for real-world use (not going to write my own linked list implementation in production) +### 4. توجہ -I may not have time to do all of these for every subject, but I'll try. +بہت سارے خلفشار ہیں جن میں قیمتی وقت لگ سکتا ہے۔ توجہ اور ارتکاز مشکل ہے۔ کچھ میوزک آن کریں۔ +دھن کے بغیر اور آپ اچھی طرح توجہ مرکوز کر سکیں گے۔ -You can see my code here: +## جو آپ نہیں سیکھیں گے + +یہ مروجہ ٹیکنالوجیز ہیں لیکن اس اسٹڈی پلان کا حصہ نہیں ہیں: + +- جاوا اسکرپٹ +- فرنٹ اینڈ ٹیکنالوجیز اور HTML، CSS +- ایس کیو ایل (SQL) + +## روزانہ کا منصوبہ + +یہ کورس بہت سارے مضامین پر مشتمل ہے۔ ہر ایک میں شاید آپ کو کچھ دن لگیں گے، یا شاید ایک ہفتہ یا اس سے بھی زیادہ۔ یہ آپ کے شیڈول پر منحصر ہے۔ + +ہر روز، فہرست سے اگلا مضمون لیں، اس موضوع کے بارے میں کچھ ویڈیوز دیکھیں، اور پھر اس ڈیٹا سٹرکچر یا الگورتھم کا، اس زبان میں جو آپ نے اس کورس کے لیے منتخب کی ہے ،کاایک کوڈ لکھیں۔ + +آپ میرا کوڈ یہاں دیکھ سکتے ہیں: - [C](https://github.com/jwasham/practice-c) - [C++](https://github.com/jwasham/practice-cpp) - [Python](https://github.com/jwasham/practice-python) -You don't need to memorize the guts of every algorithm. +آپ کو ہر الگورتھم کو حفظ کرنے کی ضرورت نہیں ہے۔ آپ کو صرف اتنا سمجھنے کی ضرورت ہے کہ آپ اپنا کوڈ لکھ سکیں۔ -Write code on a whiteboard or paper, not a computer. Test with some sample inputs. Then test it out on a computer. +## کوڈنگ سوال کی مشق -## Prerequisite Knowledge + ابھی کیوں؟ میں انٹرویو کے لیے تیار نہیں ہوں۔ -- [ ] **Learn C** - - C is everywhere. You'll see examples in books, lectures, videos, *everywhere* while you're studying. - - [ ] [C Programming Language, Vol 2](https://www.amazon.com/Programming-Language-Brian-W-Kernighan/dp/0131103628) - - This is a short book, but it will give you a great handle on the C language and if you practice it a little - you'll quickly get proficient. Understanding C helps you understand how programs and memory work. - - [answers to questions](https://github.com/lekkas/c-algorithms) +[توپھر واپس جا کر یہ پڑھیں۔](#3-do-coding-interview-questions-while-youre-learning) -- [ ] **How computers process a program:** - - [ ] [How CPU executes a program (video)](https://www.youtube.com/watch?v=XM4lGflQFvA) - - [ ] [How computers calculate - ALU (video)](https://youtu.be/1I5ZMmrOfnA) - - [ ] [Registers and RAM (video)](https://youtu.be/fpnE6UAfbtU) - - [ ] [The Central Processing Unit (CPU) (video)](https://youtu.be/FZGugFqdr60) - - [ ] [Instructions and Programs (video)](https://youtu.be/zltgXvg6r3k) +آپ کو پروگرامنگ کی مشقیں کرنے کی کیوں ضرورت ہے: +- سوال کی شناخت، اور کہاں صحیح ڈیٹا اسٹرکچر اور الگورتھم فٹ ہوتے ہیں +- سوال کے تقاضوں کو سمجھنا +- سوال کے ذریعے اپنے طریقے سے بات کرنا جیسا کہ آپ انٹرویو میں کریں گے +- کمپیوٹر کے بجائے وائٹ بورڈ یا کاغذ پر کوڈنگ +- اپنے حل کے لیے وقت اور میموری کی اصلاح کے بارے میں سوچنا (نیچے بگ-او دیکھیں) +- اپنے جوابات کی جانچ کرنا -## Algorithmic complexity / Big-O / Asymptotic analysis +یہ انٹرویو میں سوال حل کرنے کے طریقہ کار، اور بات چیت کے طریقے کا ایک بہترین تعارف ہے۔ آپ کو یہ پروگرامنگ انٹرویو کی کتابوں سے بھی ملے گا، لیکن مجھے یہ شاندار معلوم ہوا: +[الگورتھم ڈیزائن کینوس (Algorithm design canvas)](http://www.hiredintech.com/algorithm-design/) -- Nothing to implement -- There are a lot of videos here. Just watch enough until you understand it. You can always come back and review. -- If some of the lectures are too mathy, you can jump down to the bottom and watch the discrete mathematics videos to get the background knowledge. +وائٹ بورڈ یا کاغذ پر کوڈ لکھیں، کمپیوٹر پر نہیں۔ کچھ نمونے کے جوابات کے ساتھ ٹیسٹ کریں۔ پھر اسے ٹائپ کریں اور کمپیوٹر پر اس کی جانچ کریں۔ + +اگر آپ کے پاس گھر میں وائٹ بورڈ نہیں ہے تو آرٹ اسٹور سے ایک بڑا ڈرائنگ پیڈ لیں۔ آپ صوفے پر بیٹھ کر مشق کر سکتے ہیں۔ +یہ میرا "صوفہ وائٹ بورڈ" ہے۔ میں نے صرف دکھانے کے لیے تصویر میں قلم شامل کیا۔ اگر آپ قلم استعمال کرتے ہیں، تو آپ چاہیں گے کہ آپ اسے مٹابھی سکیں۔ +کیونکہ یہ جلدی گندا ہو جاتا ہے. **میں پنسل اور صافی کا استعمال کرتا ہوں۔** + +![میرا صوفہ وائٹ بورڈ](https://d3j2pkmjtin6ou.cloudfront.net/art_board_sm_2.jpg) + +**کوڈنگ سوال کی مشق پروگرامنگ کے مسائل کے جوابات کو یاد کرنے کے بارے میں نہیں ہے۔** + +## کوڈنگ کے سوالات/مسائل + +اپنی اہم کوڈنگ انٹرویو کی کتابوں کو مت بھولنا [یہاں](#interview-prep-books). + +سوالات حل کرنا: +- [حل تلاش کرنے کا طریقہ](https://www.topcoder.com/thrive/articles/How%20To%20Find%20a%20Solution) +- [ٹاپ کوڈر پرابلم اسٹیٹمنٹ کو ڈسیکٹ کرنے کا طریقہ](https://www.topcoder.com/thrive/articles/How%20To%20Dissect%20a%20Topcoder%20Problem%20Statement%20Content) + +کوڈنگ انٹرویو سوال کی ویڈیوز: +- [IDeserve (88 ویڈیوز)](https://www.youtube.com/playlist?list=PLamzFoFxwoNjPfxzaWqs7cZGsPYy0x_gI) +- [Tushar Roy (5 پلے لسٹس)](https://www.youtube.com/user/tusharroy2525/playlists?shelf_id=2&view=50&sort=dd) + - سوالات کے حل کے لیے بہترین +- [Nick White - LeetCode Solutions (187 ویڈیوز)](https://www.youtube.com/playlist?list=PLU_sdQYzUj2keVENTP0a5rdykRSgg9Wp-) + - حل اور کوڈ کی اچھی وضاحت + - آپ مختصر وقت میں کئی دیکھ سکتے ہیں۔ +- [FisherCoder - LeetCode Solutions](https://youtube.com/FisherCoder) + +چیلنج/پریکٹس سائٹس: +- [لیٹ کوڈ(LeetCode)](https://leetcode.com/) + - میری پسندیدہ کوڈنگ سوالات کی سائٹ۔ یہ کم از کم 1-2 مہینوں کے لئے(جن میں آپ تیاری کر رہے ہوں گے) سبسکرپشن کی رقم کے قابل ہے۔ + - کوڈ واک تھرو کے لیے اوپر نک وائٹ اور فشر کوڈر کی ویڈیوز دیکھیں۔ +- [ہیکر رینک (HackerRank)](https://www.hackerrank.com/) +- [ٹاپ کوڈر (TopCoder)](https://www.topcoder.com/) +- [کوڈفورسز(Codeforces)](https://codeforces.com/) +- [کوڈیلیٹی(Codility)](https://codility.com/programmers/) +- [گیکس فار گیکس(Geeks for Geeks)](https://practice.geeksforgeeks.org/explore/?page=1) +- [الگو ایکسپرٹ(AlgoExpert)](https://www.algoexpert.io/product) + - گوگل انجینئرز کے ذریعہ تخلیق کیا گیا، یہ آپ کی صلاحیتوں کو نکھارنے کا ایک بہترین ذریعہ بھی ہے۔ +- [پروجیکٹ یولر(Project Euler)](https://projecteuler.net/) + - بہت زیادہ ریاضی پر مرکوز ہے، اور انٹرویو کوڈنگ کے لیے واقعی موزوں نہیں ہے۔ + +## آو شروع کریں + +باتیں کافی ہیں، آئیے اب سیکھتے ہیں! + +لیکن سیکھتے وقت اوپر سے کوڈنگ سوالات کرنا نہ بھولیں! + +## الگورتھمک پیچیدگی / بگ-او / اسیمپٹوٹک تجزیہ + +- یہاں کرنے کو کچھ نہیں، آپ صرف ویڈیوز دیکھیں گے اور نوٹ لیں گے! آہا! +- یہاں بہت ساری ویڈیوز ہیں۔ صرف اس وقت تک دیکھیں جب تک آپ اسے سمجھ سکیں۔ آپ ہمیشہ واپس آ کر نظر ثانی کر سکتے ہیں۔ +- پریشان نہ ہوں اگر آپ اس کے پیچھے کی تمام ریاضی کو نہیں سمجھتے ہیں۔ +- آپ کو صرف یہ سمجھنے کی ضرورت ہے کہ بگ-او کے لحاظ سے الگورتھم کی پیچیدگی کو کیسے ظاہر کیا جائے۔ - [ ] [Harvard CS50 - Asymptotic Notation (video)](https://www.youtube.com/watch?v=iOq5kSKqeR4) - [ ] [Big O Notations (general quick tutorial) (video)](https://www.youtube.com/watch?v=V6mKVRU1evU) - [ ] [Big O Notation (and Omega and Theta) - best mathematical explanation (video)](https://www.youtube.com/watch?v=ei-A_wy5Yxw&index=2&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN) -- [ ] Skiena: - - [video](https://www.youtube.com/watch?v=gSyDMtdPNpU&index=2&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) - - [slides](http://www3.cs.stonybrook.edu/~algorith/video-lectures/2007/lecture2.pdf) -- [ ] [A Gentle Introduction to Algorithm Complexity Analysis](http://discrete.gr/complexity/) -- [ ] [Orders of Growth (video)](https://www.coursera.org/lecture/algorithmic-thinking-1/orders-of-growth-6PKkX) -- [ ] [Asymptotics (video)](https://www.coursera.org/lecture/algorithmic-thinking-1/asymptotics-bXAtM) +- [ ] [Skiena (video)](https://www.youtube.com/watch?v=z1mkCe3kVUA) - [ ] [UC Berkeley Big O (video)](https://archive.org/details/ucberkeley_webcast_VIS4YDpuP98) -- [ ] [UC Berkeley Big Omega (video)](https://archive.org/details/ucberkeley_webcast_ca3e7UVmeUc) - [ ] [Amortized Analysis (video)](https://www.youtube.com/watch?v=B3SpQZaAZP4&index=10&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN) -- [ ] [Illustrating "Big O" (video)](https://www.coursera.org/lecture/algorithmic-thinking-1/illustrating-big-o-YVqzv) - [ ] TopCoder (includes recurrence relations and master theorem): - - [Computational Complexity: Section 1](https://www.topcoder.com/community/competitive-programming/tutorials/computational-complexity-section-1/) - - [Computational Complexity: Section 2](https://www.topcoder.com/community/competitive-programming/tutorials/computational-complexity-section-2/) + - [Computational Complexity: Section 1](https://www.topcoder.com/thrive/articles/Computational%20Complexity%20part%20one) + - [Computational Complexity: Section 2](https://www.topcoder.com/thrive/articles/Computational%20Complexity%20part%20two) - [ ] [Cheat sheet](http://bigocheatsheet.com/) - [ ] [[Review] Big-O notation in 5 minutes (video)](https://youtu.be/__vX2sjlpXU) -## Data Structures +یہ اس کے بارے میں کافی ہے. + +جب آپ "کریکنگ دی کوڈنگ انٹرویو" سے گزرتے ہیں، تو اس پر ایک باب ہوتا ہے، اور آخر میں یہ دیکھنے کے لیے ایک کوئز ہوتا ہے کہ آپ مختلف الگورتھم کی رن ٹائم پیچیدگی کی شناخت کر سکتے ہیں یانہیں۔ یہ ایک زبردست جائزہ اور ٹیسٹ ہے۔ + +## ڈیٹا سٹرکچرز - ### Arrays - - Implement an automatically resizing vector. - - [ ] Description: - - [Arrays (video)](https://www.coursera.org/learn/data-structures/lecture/OsBSF/arrays) + - [ ] About Arrays: + - [Arrays CS50 Harvard University](https://www.youtube.com/watch?v=tI_tIZFyKBw&t=3009s) + - [Arrays (video)](https://www.coursera.org/lecture/data-structures/arrays-OsBSF) - [UC Berkeley CS61B - Linear and Multi-Dim Arrays (video)](https://archive.org/details/ucberkeley_webcast_Wp8oiO_CZZE) (Start watching from 15m 32s) - - [Dynamic Arrays (video)](https://www.coursera.org/learn/data-structures/lecture/EwbnV/dynamic-arrays) + - [Dynamic Arrays (video)](https://www.coursera.org/lecture/data-structures/dynamic-arrays-EwbnV) - [Jagged Arrays (video)](https://www.youtube.com/watch?v=1jtrQqYpt7g) - [ ] Implement a vector (mutable array with automatic resizing): - [ ] Practice coding using arrays and pointers, and pointer math to jump to an index instead of using indexing. - - [ ] new raw data array with allocated memory + - [ ] New raw data array with allocated memory - can allocate int array under the hood, just not use its features - start with 16, or if starting number is greater, use power of 2 - 16, 32, 64, 128 - [ ] size() - number of items @@ -530,21 +598,22 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input - ### Linked Lists - [ ] Description: - - [ ] [Singly Linked Lists (video)](https://www.coursera.org/learn/data-structures/lecture/kHhgK/singly-linked-lists) + - [ ] [Linked Lists CS50 Harvard University](https://www.youtube.com/watch?v=2T-A_GFuoTo&t=650s) - this builds the intuition. + - [ ] [Singly Linked Lists (video)](https://www.coursera.org/lecture/data-structures/singly-linked-lists-kHhgK) - [ ] [CS 61B - Linked Lists 1 (video)](https://archive.org/details/ucberkeley_webcast_htzJdKoEmO0) - [ ] [CS 61B - Linked Lists 2 (video)](https://archive.org/details/ucberkeley_webcast_-c4I3gFYe3w) - [ ] [[Review] Linked lists in 4 minutes (video)](https://youtu.be/F8AbOfQwl1c) - [ ] [C Code (video)](https://www.youtube.com/watch?v=QN6FPiD0Gzo) - - not the whole video, just portions about Node struct and memory allocation. + - not the whole video, just portions about Node struct and memory allocation - [ ] Linked List vs Arrays: - - [Core Linked Lists Vs Arrays (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/rjBs9/core-linked-lists-vs-arrays) - - [In The Real World Linked Lists Vs Arrays (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/QUaUd/in-the-real-world-lists-vs-arrays) - - [ ] [why you should avoid linked lists (video)](https://www.youtube.com/watch?v=YQs6IC-vgmo) + - [Core Linked Lists Vs Arrays (video)](https://www.coursera.org/lecture/data-structures-optimizing-performance/core-linked-lists-vs-arrays-rjBs9) + - [In The Real World Linked Lists Vs Arrays (video)](https://www.coursera.org/lecture/data-structures-optimizing-performance/in-the-real-world-lists-vs-arrays-QUaUd) + - [ ] [Why you should avoid linked lists (video)](https://www.youtube.com/watch?v=YQs6IC-vgmo) - [ ] Gotcha: you need pointer to pointer knowledge: (for when you pass a pointer to a function that may change the address where that pointer points) This page is just to get a grasp on ptr to ptr. I don't recommend this list traversal style. Readability and maintainability suffer due to cleverness. - [Pointers to Pointers](https://www.eskimo.com/~scs/cclass/int/sx8.html) - - [ ] implement (I did with tail pointer & without): + - [ ] Implement (I did with tail pointer & without): - [ ] size() - returns number of data elements in list - [ ] empty() - bool returns true if empty - [ ] value_at(index) - returns the value of the nth item (starting at 0 for first) @@ -560,13 +629,13 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input - [ ] reverse() - reverses the list - [ ] remove_value(value) - removes the first item in the list with this value - [ ] Doubly-linked List - - [Description (video)](https://www.coursera.org/learn/data-structures/lecture/jpGKD/doubly-linked-lists) + - [Description (video)](https://www.coursera.org/lecture/data-structures/doubly-linked-lists-jpGKD) - No need to implement -- ### Stack - - [ ] [Stacks (video)](https://www.coursera.org/learn/data-structures/lecture/UdKzQ/stacks) +- ### Stacks + - [ ] [Stacks (video)](https://www.coursera.org/lecture/data-structures/stacks-UdKzQ) - [ ] [[Review] Stacks in 3 minutes (video)](https://youtu.be/KcT3aVgrrpU) - - [ ] Will not implement. Implementing with array is trivial. + - [ ] Will not implement. Implementing with array is trivial - ### Queue - [ ] [Queue (video)](https://www.coursera.org/lecture/data-structures/queues-EShpq) @@ -588,44 +657,46 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input - dequeue: O(1) (linked list and array) - empty: O(1) (linked list and array) -- ### Hash table +- ### Hash Table - [ ] Videos: - [ ] [Hashing with Chaining (video)](https://www.youtube.com/watch?v=0M_kIqhwbFo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=8) - [ ] [Table Doubling, Karp-Rabin (video)](https://www.youtube.com/watch?v=BRO7mVIFt08&index=9&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) - [ ] [Open Addressing, Cryptographic Hashing (video)](https://www.youtube.com/watch?v=rvdJDijO2Ro&index=10&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) - [ ] [PyCon 2010: The Mighty Dictionary (video)](https://www.youtube.com/watch?v=C4Kc8xzcA68) + - [ ] [PyCon 2017: The Dictionary Even Mightier (video)](https://www.youtube.com/watch?v=66P5FMkWoVU) - [ ] [(Advanced) Randomization: Universal & Perfect Hashing (video)](https://www.youtube.com/watch?v=z0lJ2k0sl1g&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=11) - [ ] [(Advanced) Perfect hashing (video)](https://www.youtube.com/watch?v=N0COwN14gt0&list=PL2B4EEwhKD-NbwZ4ezj7gyc_3yNrojKM9&index=4) - [ ] [[Review] Hash tables in 4 minutes (video)](https://youtu.be/knV86FlSXJ8) - [ ] Online Courses: - - [ ] [Core Hash Tables (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/m7UuP/core-hash-tables) + - [ ] [Core Hash Tables (video)](https://www.coursera.org/lecture/data-structures-optimizing-performance/core-hash-tables-m7UuP) - [ ] [Data Structures (video)](https://www.coursera.org/learn/data-structures/home/week/4) - - [ ] [Phone Book Problem (video)](https://www.coursera.org/learn/data-structures/lecture/NYZZP/phone-book-problem) + - [ ] [Phone Book Problem (video)](https://www.coursera.org/lecture/data-structures/phone-book-problem-NYZZP) - [ ] distributed hash tables: - - [Instant Uploads And Storage Optimization In Dropbox (video)](https://www.coursera.org/learn/data-structures/lecture/DvaIb/instant-uploads-and-storage-optimization-in-dropbox) - - [Distributed Hash Tables (video)](https://www.coursera.org/learn/data-structures/lecture/tvH8H/distributed-hash-tables) + - [Instant Uploads And Storage Optimization In Dropbox (video)](https://www.coursera.org/lecture/data-structures/instant-uploads-and-storage-optimization-in-dropbox-DvaIb) + - [Distributed Hash Tables (video)](https://www.coursera.org/lecture/data-structures/distributed-hash-tables-tvH8H) - - [ ] implement with array using linear probing + - [ ] Implement with array using linear probing - hash(k, m) - m is size of hash table - add(key, value) - if key already exists, update value - exists(key) - get(key) - remove(key) -## More Knowledge +## مزید معلومات - ### Binary search - [ ] [Binary Search (video)](https://www.youtube.com/watch?v=D5SrAga1pno) - [ ] [Binary Search (video)](https://www.khanacademy.org/computing/computer-science/algorithms/binary-search/a/binary-search) - - [ ] [detail](https://www.topcoder.com/community/competitive-programming/tutorials/binary-search/) + - [ ] [detail](https://www.topcoder.com/thrive/articles/Binary%20Search) + - [ ] [blueprint](https://leetcode.com/discuss/general-discussion/786126/python-powerful-ultimate-binary-search-template-solved-many-problems) - [ ] [[Review] Binary search in 4 minutes (video)](https://youtu.be/fDKIpRe8GW4) - [ ] Implement: - binary search (on sorted array of integers) - binary search using recursion - ### Bitwise operations - - [ ] [Bits cheat sheet](https://github.com/jwasham/coding-interview-university/blob/master/extras/cheat%20sheets/bits-cheat-cheet.pdf) - you should know many of the powers of 2 from (2^1 to 2^16 and 2^32) + - [ ] [Bits cheat sheet](https://github.com/jwasham/coding-interview-university/blob/main/extras/cheat%20sheets/bits-cheat-sheet.pdf) - you should know many of the powers of 2 from (2^1 to 2^16 and 2^32) - [ ] Get a really good understanding of manipulating bits with: &, |, ^, ~, >>, << - [ ] [words](https://en.wikipedia.org/wiki/Word_(computer_architecture)) - [ ] Good intro: @@ -636,27 +707,26 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input - [ ] [Bithacks](https://graphics.stanford.edu/~seander/bithacks.html) - [ ] [The Bit Twiddler](https://bits.stephan-brumme.com/) - [ ] [The Bit Twiddler Interactive](https://bits.stephan-brumme.com/interactive.html) + - [ ] [Bit Hacks (video)](https://www.youtube.com/watch?v=ZusiKXcz_ac) + - [ ] [Practice Operations](https://pconrad.github.io/old_pconrad_cs16/topics/bitOps/) - [ ] 2s and 1s complement - [Binary: Plusses & Minuses (Why We Use Two's Complement) (video)](https://www.youtube.com/watch?v=lKTsv6iVxV4) - [1s Complement](https://en.wikipedia.org/wiki/Ones%27_complement) - [2s Complement](https://en.wikipedia.org/wiki/Two%27s_complement) - - [ ] count set bits + - [ ] Count set bits - [4 ways to count bits in a byte (video)](https://youtu.be/Hzuzo9NJrlc) - [Count Bits](https://graphics.stanford.edu/~seander/bithacks.html#CountBitsSetKernighan) - [How To Count The Number Of Set Bits In a 32 Bit Integer](http://stackoverflow.com/questions/109023/how-to-count-the-number-of-set-bits-in-a-32-bit-integer) - - [ ] swap values: + - [ ] Swap values: - [Swap](https://bits.stephan-brumme.com/swap.html) - - [ ] absolute value: + - [ ] Absolute value: - [Absolute Integer](https://bits.stephan-brumme.com/absInteger.html) ## Trees -- ### Trees - Notes & Background - - [ ] [Series: Core Trees (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/ovovP/core-trees) - - [ ] [Series: Trees (video)](https://www.coursera.org/learn/data-structures/lecture/95qda/trees) - - basic tree construction - - traversal - - manipulation algorithms +- ### Trees - Intro + - [ ] [Intro to Trees (video)](https://www.coursera.org/lecture/data-structures/trees-95qda) + - [ ] [Tree Traversal (video)](https://www.coursera.org/lecture/data-structures/tree-traversal-fr51b) - [ ] [BFS(breadth-first search) and DFS(depth-first search) (video)](https://www.youtube.com/watch?v=uWL6FJhq5fM) - BFS notes: - level order (BFS, using queue) @@ -675,11 +745,9 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input - [ ] [[Review] Tree Traversal (playlist) in 11 minutes (video)](https://www.youtube.com/playlist?list=PL9xmBV_5YoZO1JC2RgEi04nLy6D-rKk6b) - ### Binary search trees: BSTs - - [ ] [Binary Search Tree Review (video)](https://www.youtube.com/watch?v=x6At0nzX92o&index=1&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6) - - [ ] [Series (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/p82sw/core-introduction-to-binary-search-trees) - - starts with symbol table and goes through BST applications + - [ ] [Binary Search Tree Review (video)](https://www.youtube.com/watch?v=x6At0nzX92o&index=1&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6) - [ ] [Introduction (video)](https://www.coursera.org/learn/data-structures/lecture/E7cXP/introduction) - - [ ] [MIT (video)](https://www.youtube.com/watch?v=9Jry5-82I68) + - [ ] [MIT (video)](https://www.youtube.com/watch?v=76dhtgZt38A&ab_channel=MITOpenCourseWare) - C/C++: - [ ] [Binary search tree - Implementation in C/C++ (video)](https://www.youtube.com/watch?v=COZK7NATh4k&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=28) - [ ] [BST implementation - memory allocation in stack and heap (video)](https://www.youtube.com/watch?v=hWokyBoo0aI&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=29) @@ -707,16 +775,15 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input - ### Heap / Priority Queue / Binary Heap - visualized as a tree, but is usually linear in storage (array, linked list) - [ ] [Heap](https://en.wikipedia.org/wiki/Heap_(data_structure)) - - [ ] [Introduction (video)](https://www.coursera.org/learn/data-structures/lecture/2OpTs/introduction) - - [ ] [Naive Implementations (video)](https://www.coursera.org/learn/data-structures/lecture/z3l9N/naive-implementations) + - [ ] [Introduction (video)](https://www.coursera.org/lecture/data-structures/introduction-2OpTs) - [ ] [Binary Trees (video)](https://www.coursera.org/learn/data-structures/lecture/GRV2q/binary-trees) - [ ] [Tree Height Remark (video)](https://www.coursera.org/learn/data-structures/supplement/S5xxz/tree-height-remark) - [ ] [Basic Operations (video)](https://www.coursera.org/learn/data-structures/lecture/0g1dl/basic-operations) - [ ] [Complete Binary Trees (video)](https://www.coursera.org/learn/data-structures/lecture/gl5Ni/complete-binary-trees) - [ ] [Pseudocode (video)](https://www.coursera.org/learn/data-structures/lecture/HxQo9/pseudocode) - [ ] [Heap Sort - jumps to start (video)](https://youtu.be/odNJmw5TOEE?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3291) - - [ ] [Heap Sort (video)](https://www.coursera.org/learn/data-structures/lecture/hSzMO/heap-sort) - - [ ] [Building a heap (video)](https://www.coursera.org/learn/data-structures/lecture/dwrOS/building-a-heap) + - [ ] [Heap Sort (video)](https://www.coursera.org/lecture/data-structures/heap-sort-hSzMO) + - [ ] [Building a heap (video)](https://www.coursera.org/lecture/data-structures/building-a-heap-dwrOS) - [ ] [MIT: Heaps and Heap Sort (video)](https://www.youtube.com/watch?v=B7hVxCmfPtM&index=4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) - [ ] [CS 61B Lecture 24: Priority Queues (video)](https://archive.org/details/ucberkeley_webcast_yIUFT6AKBGE) - [ ] [Linear Time BuildHeap (max-heap)](https://www.youtube.com/watch?v=MiyLo8adrWw) @@ -729,17 +796,16 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input - [ ] is_empty() - returns true if heap contains no elements - [ ] extract_max - returns the max item, removing it - [ ] sift_down - needed for extract_max - - [ ] remove(i) - removes item at index x + - [ ] remove(x) - removes item at index x - [ ] heapify - create a heap from an array of elements, needed for heap_sort - - [ ] heap_sort() - take an unsorted array and turn it into a sorted array in-place using a max heap - - note: using a min heap instead would save operations, but double the space needed (cannot do in-place). + - [ ] heap_sort() - take an unsorted array and turn it into a sorted array in-place using a max heap or min heap ## Sorting - [ ] Notes: - Implement sorts & know best case/worst case, average complexity of each: - no bubble sort - it's terrible - O(n^2), except when n <= 16 - - [ ] stability in sorting algorithms ("Is Quicksort stable?") + - [ ] Stability in sorting algorithms ("Is Quicksort stable?") - [Sorting Algorithm Stability](https://en.wikipedia.org/wiki/Sorting_algorithm#Stability) - [Stability In Sorting Algorithms](http://stackoverflow.com/questions/1517793/stability-in-sorting-algorithms) - [Stability In Sorting Algorithms](http://www.geeksforgeeks.org/stability-in-sorting-algorithms/) @@ -748,26 +814,27 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input - I wouldn't recommend sorting a linked list, but merge sort is doable. - [Merge Sort For Linked List](http://www.geeksforgeeks.org/merge-sort-for-linked-list/) -- For heapsort, see Heap data structure above. Heap sort is great, but not stable. +- For heapsort, see Heap data structure above. Heap sort is great, but not stable - [ ] [Sedgewick - Mergesort (5 videos)](https://www.coursera.org/learn/algorithms-part1/home/week/3) - - [ ] [1. Mergesort](https://www.coursera.org/learn/algorithms-part1/lecture/ARWDq/mergesort) + - [ ] [1. Mergesort](https://www.coursera.org/lecture/algorithms-part1/mergesort-ARWDq) - [ ] [2. Bottom up Mergesort](https://www.coursera.org/learn/algorithms-part1/lecture/PWNEl/bottom-up-mergesort) - - [ ] [3. Sorting Complexity](https://www.coursera.org/learn/algorithms-part1/lecture/xAltF/sorting-complexity) - - [ ] [4. Comparators](https://www.coursera.org/learn/algorithms-part1/lecture/9FYhS/comparators) + - [ ] [3. Sorting Complexity](https://www.coursera.org/lecture/algorithms-part1/sorting-complexity-xAltF) + - [ ] [4. Comparators](https://www.coursera.org/lecture/algorithms-part1/comparators-9FYhS) - [ ] [5. Stability](https://www.coursera.org/learn/algorithms-part1/lecture/pvvLZ/stability) - [ ] [Sedgewick - Quicksort (4 videos)](https://www.coursera.org/learn/algorithms-part1/home/week/3) - - [ ] [1. Quicksort](https://www.coursera.org/learn/algorithms-part1/lecture/vjvnC/quicksort) - - [ ] [2. Selection](https://www.coursera.org/learn/algorithms-part1/lecture/UQxFT/selection) - - [ ] [3. Duplicate Keys](https://www.coursera.org/learn/algorithms-part1/lecture/XvjPd/duplicate-keys) - - [ ] [4. System Sorts](https://www.coursera.org/learn/algorithms-part1/lecture/QBNZ7/system-sorts) + - [ ] [1. Quicksort](https://www.coursera.org/lecture/algorithms-part1/quicksort-vjvnC) + - [ ] [2. Selection](https://www.coursera.org/lecture/algorithms-part1/selection-UQxFT) + - [ ] [3. Duplicate Keys](https://www.coursera.org/lecture/algorithms-part1/duplicate-keys-XvjPd) + - [ ] [4. System Sorts](https://www.coursera.org/lecture/algorithms-part1/system-sorts-QBNZ7) - [ ] UC Berkeley: - [ ] [CS 61B Lecture 29: Sorting I (video)](https://archive.org/details/ucberkeley_webcast_EiUvYS2DT6I) - [ ] [CS 61B Lecture 30: Sorting II (video)](https://archive.org/details/ucberkeley_webcast_2hTY3t80Qsk) - [ ] [CS 61B Lecture 32: Sorting III (video)](https://archive.org/details/ucberkeley_webcast_Y6LOLpxg6Dc) - [ ] [CS 61B Lecture 33: Sorting V (video)](https://archive.org/details/ucberkeley_webcast_qNMQ4ly43p4) + - [ ] [CS 61B 2014-04-21: Radix Sort(video)](https://archive.org/details/ucberkeley_webcast_pvbBMd-3NoI) - [ ] [Bubble Sort (video)](https://www.youtube.com/watch?v=P00xJgWzz2c&index=1&list=PL89B61F78B552C1AB) - [ ] [Analyzing Bubble Sort (video)](https://www.youtube.com/watch?v=ni_zk257Nqo&index=7&list=PL89B61F78B552C1AB) @@ -798,15 +865,15 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input - [ ] Mergesort: O(n log n) average and worst case - [ ] Quicksort O(n log n) average case - Selection sort and insertion sort are both O(n^2) average and worst case - - For heapsort, see Heap data structure above. + - For heapsort, see Heap data structure above - [ ] Not required, but I recommended them: - [ ] [Sedgewick - Radix Sorts (6 videos)](https://www.coursera.org/learn/algorithms-part2/home/week/3) - [ ] [1. Strings in Java](https://www.coursera.org/learn/algorithms-part2/lecture/vGHvb/strings-in-java) - - [ ] [2. Key Indexed Counting](https://www.coursera.org/learn/algorithms-part2/lecture/2pi1Z/key-indexed-counting) + - [ ] [2. Key Indexed Counting](https://www.coursera.org/lecture/algorithms-part2/key-indexed-counting-2pi1Z) - [ ] [3. Least Significant Digit First String Radix Sort](https://www.coursera.org/learn/algorithms-part2/lecture/c1U7L/lsd-radix-sort) - [ ] [4. Most Significant Digit First String Radix Sort](https://www.coursera.org/learn/algorithms-part2/lecture/gFxwG/msd-radix-sort) - - [ ] [5. 3 Way Radix Quicksort](https://www.coursera.org/learn/algorithms-part2/lecture/crkd5/3-way-radix-quicksort) + - [ ] [5. 3 Way Radix Quicksort](https://www.coursera.org/lecture/algorithms-part2/3-way-radix-quicksort-crkd5) - [ ] [6. Suffix Arrays](https://www.coursera.org/learn/algorithms-part2/lecture/TH18W/suffix-arrays) - [ ] [Radix Sort](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#radixSort) - [ ] [Radix Sort (video)](https://www.youtube.com/watch?v=xhr26ia4k38) @@ -819,41 +886,40 @@ If you need more detail on this subject, see "Sorting" section in [Additional De ## Graphs -Graphs can be used to represent many problems in computer science, so this section is long, like trees and sorting were. +گراف کو کمپیوٹر سائنس میں بہت سے مسائل کی نمائندگی کرنے کے لیے استعمال کیا جا سکتا ہے، اس لیے یہ سیکشن لمبا ہے، جیسا کہ ٹریز اور ترتیب / سارٹنگ تھے۔ - Notes: - - There are 4 basic ways to represent a graph in memory: + - میموری میں گراف کی نمائندگی کرنے کے 4 بنیادی طریقے ہیں: - objects and pointers - adjacency matrix - adjacency list - adjacency map - - Familiarize yourself with each representation and its pros & cons - - BFS and DFS - know their computational complexity, their tradeoffs, and how to implement them in real code - - When asked a question, look for a graph-based solution first, then move on if none. + - ہر ایک نمائندگی اور اس کے فوائد اور نقصانات سے اپنے آپ کو واقف کریں۔ + - BFS اور DFS - ان کی کمپیوٹیشنل پیچیدگی، ان کے تجارتی معاہدوں، اور انہیں حقیقی کوڈ میں لاگو کرنے کا طریقہ جانیں۔ + - جب کوئی سوال پوچھا جائے تو پہلے گراف پر مبنی حل تلاش کریں، پھر اگر کوئی نہیں تو آگے بڑھیں۔ - [ ] MIT(videos): - - [ ] [Breadth-First Search](https://www.youtube.com/watch?v=s-CYnVz-uh4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=13) - - [ ] [Depth-First Search](https://www.youtube.com/watch?v=AfSk24UTFS8&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=14) + - [ ] [Breadth-First Search](https://www.youtube.com/watch?v=oFVYVzlvk9c&t=14s&ab_channel=MITOpenCourseWare) + - [ ] [Depth-First Search](https://www.youtube.com/watch?v=IBfWDYSffUU&t=32s&ab_channel=MITOpenCourseWare) - [ ] Skiena Lectures - great intro: - - [ ] [CSE373 2012 - Lecture 11 - Graph Data Structures (video)](https://www.youtube.com/watch?v=OiXxhDrFruw&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=11) - - [ ] [CSE373 2012 - Lecture 12 - Breadth-First Search (video)](https://www.youtube.com/watch?v=g5vF8jscteo&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=12) - - [ ] [CSE373 2012 - Lecture 13 - Graph Algorithms (video)](https://www.youtube.com/watch?v=S23W6eTcqdY&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=13) - - [ ] [CSE373 2012 - Lecture 14 - Graph Algorithms (con't) (video)](https://www.youtube.com/watch?v=WitPBKGV0HY&index=14&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) - - [ ] [CSE373 2012 - Lecture 15 - Graph Algorithms (con't 2) (video)](https://www.youtube.com/watch?v=ia1L30l7OIg&index=15&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) - - [ ] [CSE373 2012 - Lecture 16 - Graph Algorithms (con't 3) (video)](https://www.youtube.com/watch?v=jgDOQq6iWy8&index=16&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) + - [ ] [CSE373 2020 - Lecture 10 - Graph Data Structures (video)](https://www.youtube.com/watch?v=Sjk0xqWWPCc&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=10) + - [ ] [CSE373 2020 - Lecture 11 - Graph Traversal (video)](https://www.youtube.com/watch?v=ZTwjXj81NVY&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=11) + - [ ] [CSE373 2020 - Lecture 12 - Depth First Search (video)](https://www.youtube.com/watch?v=KyordYB3BOs&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=12) + - [ ] [CSE373 2020 - Lecture 13 - Minimum Spanning Trees (video)](https://www.youtube.com/watch?v=oolm2VnJUKw&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=13) + - [ ] [CSE373 2020 - Lecture 14 - Minimum Spanning Trees (con't) (video)](https://www.youtube.com/watch?v=RktgPx0MarY&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=14) + - [ ] [CSE373 2020 - Lecture 15 - Graph Algorithms (con't 2) (video)](https://www.youtube.com/watch?v=MUe5DXRhyAo&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=15) - [ ] Graphs (review and more): - [ ] [6.006 Single-Source Shortest Paths Problem (video)](https://www.youtube.com/watch?v=Aa2sqUhIn-E&index=15&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) - - [ ] [6.006 Dijkstra (video)](https://www.youtube.com/watch?v=2E7MmKv0Y24&index=16&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) - - [ ] [6.006 Bellman-Ford (video)](https://www.youtube.com/watch?v=ozsuci5pIso&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=17) + - [ ] [6.006 Dijkstra (video)](https://www.youtube.com/watch?v=NSHizBK9JD8&t=1731s&ab_channel=MITOpenCourseWare) + - [ ] [6.006 Bellman-Ford (video)](https://www.youtube.com/watch?v=f9cVS_URPc0&ab_channel=MITOpenCourseWare) - [ ] [6.006 Speeding Up Dijkstra (video)](https://www.youtube.com/watch?v=CHvQ3q_gJ7E&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=18) - [ ] [Aduni: Graph Algorithms I - Topological Sorting, Minimum Spanning Trees, Prim's Algorithm - Lecture 6 (video)]( https://www.youtube.com/watch?v=i_AQT_XfvD8&index=6&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm) - [ ] [Aduni: Graph Algorithms II - DFS, BFS, Kruskal's Algorithm, Union Find Data Structure - Lecture 7 (video)]( https://www.youtube.com/watch?v=ufj5_bppBsA&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=7) - [ ] [Aduni: Graph Algorithms III: Shortest Path - Lecture 8 (video)](https://www.youtube.com/watch?v=DiedsPsMKXc&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=8) - [ ] [Aduni: Graph Alg. IV: Intro to geometric algorithms - Lecture 9 (video)](https://www.youtube.com/watch?v=XIAQRlNkJAw&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=9) - - [ ] ~~[CS 61B 2014 (starting at 58:09) (video)](https://youtu.be/dgjX4HdMI-Q?list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd&t=3489)~~ - [ ] [CS 61B 2014: Weighted graphs (video)](https://archive.org/details/ucberkeley_webcast_zFbq8vOZ_0k) - [ ] [Greedy Algorithms: Minimum Spanning Tree (video)](https://www.youtube.com/watch?v=tKwnms5iRBU&index=16&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) - [ ] [Strongly Connected Components Kosaraju's Algorithm Graph Algorithm (video)](https://www.youtube.com/watch?v=RpgcYiky7uw) @@ -879,7 +945,7 @@ Graphs can be used to represent many problems in computer science, so this secti - [ ] list strongly connected components - [ ] check for bipartite graph -## Even More Knowledge +## اس سے بھی زیادہ معلومات - ### Recursion - [ ] Stanford lectures on recursion & backtracking: @@ -887,21 +953,25 @@ Graphs can be used to represent many problems in computer science, so this secti - [ ] [Lecture 9 | Programming Abstractions (video)](https://www.youtube.com/watch?v=uFJhEPrbycQ&list=PLFE6E58F856038C69&index=9) - [ ] [Lecture 10 | Programming Abstractions (video)](https://www.youtube.com/watch?v=NdF1QDTRkck&index=10&list=PLFE6E58F856038C69) - [ ] [Lecture 11 | Programming Abstractions (video)](https://www.youtube.com/watch?v=p-gpaIGRCQI&list=PLFE6E58F856038C69&index=11) - - when it is appropriate to use it - - how is tail recursion better than not? + - When it is appropriate to use it? + - How is tail recursion better than not? - [ ] [What Is Tail Recursion Why Is It So Bad?](https://www.quora.com/What-is-tail-recursion-Why-is-it-so-bad) - [ ] [Tail Recursion (video)](https://www.coursera.org/lecture/programming-languages/tail-recursion-YZic1) - + - [ ] [5 Simple Steps for Solving Any Recursive Problem(video)](https://youtu.be/ngCos392W4w) + + Backtracking Blueprint: [Java](https://leetcode.com/problems/combination-sum/discuss/16502/A-general-approach-to-backtracking-questions-in-Java-(Subsets-Permutations-Combination-Sum-Palindrome-Partitioning)) + [Python](https://leetcode.com/problems/combination-sum/discuss/429538/General-Backtracking-questions-solutions-in-Python-for-reference-%3A) - ### Dynamic Programming - - You probably won't see any dynamic programming problems in your interview, but it's worth being able to recognize a problem as being a candidate for dynamic programming. + - You probably won't see any dynamic programming problems in your interview, but it's worth being able to recognize a + problem as being a candidate for dynamic programming. - This subject can be pretty difficult, as each DP soluble problem must be defined as a recursion relation, and coming up with it can be tricky. - I suggest looking at many examples of DP problems until you have a solid understanding of the pattern involved. - [ ] Videos: - - the Skiena videos can be hard to follow since he sometimes uses the whiteboard, which is too small to see - - [ ] [Skiena: CSE373 2012 - Lecture 19 - Introduction to Dynamic Programming (video)](https://youtu.be/Qc2ieXRgR0k?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1718) - - [ ] [Skiena: CSE373 2012 - Lecture 20 - Edit Distance (video)](https://youtu.be/IsmMhMdyeGY?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=2749) - - [ ] [Skiena: CSE373 2012 - Lecture 21 - Dynamic Programming Examples (video)](https://youtu.be/o0V9eYF4UI8?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=406) - - [ ] [Skiena: CSE373 2012 - Lecture 22 - Applications of Dynamic Programming (video)](https://www.youtube.com/watch?v=dRbMC1Ltl3A&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=22) + - [ ] [Skiena: CSE373 2020 - Lecture 19 - Introduction to Dynamic Programming (video)](https://www.youtube.com/watch?v=wAA0AMfcJHQ&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=18) + - [ ] [Skiena: CSE373 2020 - Lecture 20 - Edit Distance (video)](https://www.youtube.com/watch?v=T3A4jlHlhtA&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=19) + - [ ] [Skiena: CSE373 2020 - Lecture 20 - Edit Distance (continued) (video)](https://www.youtube.com/watch?v=iPnPVcZmRbE&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=20) + - [ ] [Skiena: CSE373 2020 - Lecture 21 - Dynamic Programming (video)](https://www.youtube.com/watch?v=2xPE4Wq8coQ&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=21) + - [ ] [Skiena: CSE373 2020 - Lecture 22 - Dynamic Programming and Review (video)](https://www.youtube.com/watch?v=Yh3RzqQGsyI&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=22) - [ ] [Simonson: Dynamic Programming 0 (starts at 59:18) (video)](https://youtu.be/J5aJEcOr6Eo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3558) - [ ] [Simonson: Dynamic Programming I - Lecture 11 (video)](https://www.youtube.com/watch?v=0EzHjQ_SOeU&index=11&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm) - [ ] [Simonson: Dynamic programming II - Lecture 12 (video)](https://www.youtube.com/watch?v=v1qiRwuJU7g&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=12) @@ -911,17 +981,13 @@ Graphs can be used to represent many problems in computer science, so this secti - [ ] [Dynamic Programming](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#dynamicProgramming) - [ ] Coursera: - [ ] [The RNA secondary structure problem (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/80RrW/the-rna-secondary-structure-problem) - - [ ] [A dynamic programming algorithm (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/PSonq/a-dynamic-programming-algorithm) - - [ ] [Illustrating the DP algorithm (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/oUEK2/illustrating-the-dp-algorithm) + - [ ] [A dynamic programming algorithm (video)](https://www.coursera.org/lecture/algorithmic-thinking-2/a-dynamic-programming-algorithm-PSonq) + - [ ] [Illustrating the DP algorithm (video)](https://www.coursera.org/lecture/algorithmic-thinking-2/illustrating-the-dp-algorithm-oUEK2) - [ ] [Running time of the DP algorithm (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/nfK2r/running-time-of-the-dp-algorithm) - [ ] [DP vs. recursive implementation (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/M999a/dp-vs-recursive-implementation) - - [ ] [Global pairwise sequence alignment (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/UZ7o6/global-pairwise-sequence-alignment) + - [ ] [Global pairwise sequence alignment (video)](https://www.coursera.org/lecture/algorithmic-thinking-2/global-pairwise-sequence-alignment-UZ7o6) - [ ] [Local pairwise sequence alignment (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/WnNau/local-pairwise-sequence-alignment) -- ### Object-Oriented Programming - - [ ] [Optional: UML 2.0 Series (video)](https://www.youtube.com/watch?v=OkC7HKtiZC0&list=PLGLfVvz_LVvQ5G-LdJ8RLqe-ndo7QITYc) - - [ ] SOLID OOP Principles: [SOLID Principles (video)](https://www.youtube.com/playlist?list=PL4CE9F710017EA77A) - - ### Design patterns - [ ] [Quick UML review (video)](https://www.youtube.com/watch?v=3cmzqZzwNDM&list=PLGLfVvz_LVvQ5G-LdJ8RLqe-ndo7QITYc&index=3) - [ ] Learn these patterns: @@ -942,15 +1008,10 @@ Graphs can be used to represent many problems in computer science, so this secti - [ ] iterator - [ ] composite - [ ] flyweight - - [ ] [Chapter 6 (Part 1) - Patterns (video)](https://youtu.be/LAP2A80Ajrg?list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO&t=3344) - - [ ] [Chapter 6 (Part 2) - Abstraction-Occurrence, General Hierarchy, Player-Role, Singleton, Observer, Delegation (video)](https://www.youtube.com/watch?v=U8-PGsjvZc4&index=12&list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO) - - [ ] [Chapter 6 (Part 3) - Adapter, Facade, Immutable, Read-Only Interface, Proxy (video)](https://www.youtube.com/watch?v=7sduBHuex4c&index=13&list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO) - [ ] [Series of videos (27 videos)](https://www.youtube.com/playlist?list=PLF206E906175C7E07) - - [ ] [Head First Design Patterns](https://www.amazon.com/Head-First-Design-Patterns-Freeman/dp/0596007124) + - [ ] [Book: Head First Design Patterns](https://www.amazon.com/Head-First-Design-Patterns-Freeman/dp/0596007124) - I know the canonical book is "Design Patterns: Elements of Reusable Object-Oriented Software", but Head First is great for beginners to OO. - - [ ] [Handy reference: 101 Design Patterns & Tips for Developers](https://sourcemaking.com/design-patterns-and-tips) - - [ ] [Design patterns for humans](https://github.com/kamranahmedse/design-patterns-for-humans#structural-design-patterns) - + - [Handy reference: 101 Design Patterns & Tips for Developers](https://sourcemaking.com/design-patterns-and-tips) - ### Combinatorics (n choose k) & Probability - [ ] [Math Skills: How to find Factorial, Permutation and Combination (Choose) (video)](https://www.youtube.com/watch?v=8RRo6Ti9d0U) @@ -973,9 +1034,10 @@ Graphs can be used to represent many problems in computer science, so this secti - [ ] [NP Completeness III (Video)](https://www.youtube.com/watch?v=fCX1BGT3wjE&index=17&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm) - [ ] [NP Completeness IV (video)](https://www.youtube.com/watch?v=NKLDp3Rch3M&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=18) - [ ] Skiena: - - [ ] [CSE373 2012 - Lecture 23 - Introduction to NP-Completeness (video)](https://youtu.be/KiK5TVgXbFg?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1508) - - [ ] [CSE373 2012 - Lecture 24 - NP-Completeness Proofs (video)](https://www.youtube.com/watch?v=27Al52X3hd4&index=24&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) - - [ ] [CSE373 2012 - Lecture 25 - NP-Completeness Challenge (video)](https://www.youtube.com/watch?v=xCPH4gwIIXM&index=25&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) + - [ ] [CSE373 2020 - Lecture 23 - NP-Completeness (video)](https://www.youtube.com/watch?v=ItHp5laE1VE&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=23) + - [ ] [CSE373 2020 - Lecture 24 - Satisfiability (video)](https://www.youtube.com/watch?v=inaFJeCzGxU&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=24) + - [ ] [CSE373 2020 - Lecture 25 - More NP-Completeness (video)](https://www.youtube.com/watch?v=B-bhKxjZLlc&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=25) + - [ ] [CSE373 2020 - Lecture 26 - NP-Completeness Challenge (video)](https://www.youtube.com/watch?v=_EzetTkG_Cc&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=26) - [ ] [Complexity: P, NP, NP-completeness, Reductions (video)](https://www.youtube.com/watch?v=eHZifpgyH_4&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=22) - [ ] [Complexity: Approximation Algorithms (video)](https://www.youtube.com/watch?v=MEz1J9wY2iM&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=24) - [ ] [Complexity: Fixed-Parameter Algorithms (video)](https://www.youtube.com/watch?v=4q-jmGrmxKs&index=25&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) @@ -983,6 +1045,13 @@ Graphs can be used to represent many problems in computer science, so this secti - [Jupyter Notebook](http://nbviewer.jupyter.org/url/norvig.com/ipython/TSP.ipynb) - Pages 1048 - 1140 in CLRS if you have it. +- ### How computers process a program + + - [ ] [How CPU executes a program (video)](https://www.youtube.com/watch?v=XM4lGflQFvA) + - [ ] [How computers calculate - ALU (video)](https://youtu.be/1I5ZMmrOfnA) + - [ ] [Registers and RAM (video)](https://youtu.be/fpnE6UAfbtU) + - [ ] [The Central Processing Unit (CPU) (video)](https://youtu.be/FZGugFqdr60) + - [ ] [Instructions and Programs (video)](https://youtu.be/zltgXvg6r3k) - ### Caches - [ ] LRU cache: - [ ] [The Magic of LRU Cache (100 Days of Google Dev) (video)](https://www.youtube.com/watch?v=R5ON3iwx78M) @@ -999,26 +1068,27 @@ Graphs can be used to represent many problems in computer science, so this secti - [What Is The Difference Between A Process And A Thread?](https://www.quora.com/What-is-the-difference-between-a-process-and-a-thread) - Covers: - Processes, Threads, Concurrency issues - - difference between processes and threads - - processes - - threads - - locks - - mutexes - - semaphores - - monitors - - how they work - - deadlock - - livelock + - Difference between processes and threads + - Processes + - Threads + - Locks + - Mutexes + - Semaphores + - Monitors + - How they work? + - Deadlock + - Livelock - CPU activity, interrupts, context switching - Modern concurrency constructs with multicore processors - - [Paging, segmentation and virtual memory (video)](https://www.youtube.com/watch?v=LKe7xK0bF7o&list=PLCiOXwirraUCBE9i_ukL8_Kfg6XNv7Se8&index=2) - - [Interrupts (video)](https://www.youtube.com/watch?v=uFKi2-J-6II&list=PLCiOXwirraUCBE9i_ukL8_Kfg6XNv7Se8&index=3) + - [Paging, segmentation and virtual memory (video)](https://youtu.be/O4nwUqQodAg) + - [Interrupts (video)](https://youtu.be/iKlAWIKEyuw) - Process resource needs (memory: code, static storage, stack, heap, and also file descriptors, i/o) - Thread resource needs (shares above (minus stack) with other threads in the same process but each has its own pc, stack counter, registers, and stack) - Forking is really copy on write (read-only) until the new process writes to memory, then it does a full copy. - Context switching - - How context switching is initiated by the operating system and underlying hardware + - How context switching is initiated by the operating system and underlying hardware? - [ ] [threads in C++ (series - 10 videos)](https://www.youtube.com/playlist?list=PL5jc9xFGsL8E12so1wlMS0r0hTQoJL74M) + - [ ] [CS 377 Spring '14: Operating Systems from University of Massachusetts](https://www.youtube.com/playlist?list=PLacuG5pysFbDQU8kKxbUh4K5c1iL5_k7k) - [ ] concurrency in Python (videos): - [ ] [Short series on threads](https://www.youtube.com/playlist?list=PL1H1sBF1VAKVMONJWJkmUh6_p8g4F2oy1) - [ ] [Python Threads](https://www.youtube.com/watch?v=Bs7vPNbB9JM) @@ -1043,26 +1113,22 @@ Graphs can be used to represent many problems in computer science, so this secti - [ ] [Tao Of Testing](http://jasonpolites.github.io/tao-of-testing/ch3-1.1.html) - [ ] [How to write tests](http://jasonpolites.github.io/tao-of-testing/ch4-1.1.html) -- ### Scheduling - - in an OS, how it works - - can be gleaned from Operating System videos - - ### String searching & manipulations - [ ] [Sedgewick - Suffix Arrays (video)](https://www.coursera.org/learn/algorithms-part2/lecture/TH18W/suffix-arrays) - [ ] [Sedgewick - Substring Search (videos)](https://www.coursera.org/learn/algorithms-part2/home/week/4) - - [ ] [1. Introduction to Substring Search](https://www.coursera.org/learn/algorithms-part2/lecture/n3ZpG/introduction-to-substring-search) + - [ ] [1. Introduction to Substring Search](https://www.coursera.org/lecture/algorithms-part2/introduction-to-substring-search-n3ZpG) - [ ] [2. Brute-Force Substring Search](https://www.coursera.org/learn/algorithms-part2/lecture/2Kn5i/brute-force-substring-search) - [ ] [3. Knuth-Morris Pratt](https://www.coursera.org/learn/algorithms-part2/lecture/TAtDr/knuth-morris-pratt) - [ ] [4. Boyer-Moore](https://www.coursera.org/learn/algorithms-part2/lecture/CYxOT/boyer-moore) - - [ ] [5. Rabin-Karp](https://www.coursera.org/learn/algorithms-part2/lecture/3KiqT/rabin-karp) + - [ ] [5. Rabin-Karp](https://www.coursera.org/lecture/algorithms-part2/rabin-karp-3KiqT) - [ ] [Search pattern in text (video)](https://www.coursera.org/learn/data-structures/lecture/tAfHI/search-pattern-in-text) - If you need more detail on this subject, see "String Matching" section in [Additional Detail on Some Subjects](#additional-detail-on-some-subjects) + If you need more detail on this subject, see "String Matching" section in [Additional Detail on Some Subjects](#additional-detail-on-some-subjects). - ### Tries - Note there are different kinds of tries. Some have prefixes, some don't, and some use string instead of bits - to track the path. - - I read through code, but will not implement. + to track the path + - I read through code, but will not implement - [ ] [Sedgewick - Tries (3 videos)](https://www.coursera.org/learn/algorithms-part2/home/week/4) - [ ] [1. R Way Tries](https://www.coursera.org/learn/algorithms-part2/lecture/CPVdr/r-way-tries) - [ ] [2. Ternary Search Tries](https://www.coursera.org/learn/algorithms-part2/lecture/yQM8K/ternary-search-tries) @@ -1073,13 +1139,12 @@ Graphs can be used to represent many problems in computer science, so this secti - [ ] [Performance Of Tries (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/PvlZW/core-performance-of-tries) - [ ] [Implementing A Trie (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/DFvd3/core-implementing-a-trie) - [ ] [The Trie: A Neglected Data Structure](https://www.toptal.com/java/the-trie-a-neglected-data-structure) - - [ ] [TopCoder - Using Tries](https://www.topcoder.com/community/competitive-programming/tutorials/using-tries/) + - [ ] [TopCoder - Using Tries](https://www.topcoder.com/thrive/articles/Using%20Tries) - [ ] [Stanford Lecture (real world use case) (video)](https://www.youtube.com/watch?v=TJ8SkcUSdbU) - [ ] [MIT, Advanced Data Structures, Strings (can get pretty obscure about halfway through) (video)](https://www.youtube.com/watch?v=NinWEPPrkDQ&index=16&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf) - ### Floating Point Numbers - [ ] simple 8-bit: [Representation of Floating Point Numbers - 1 (video - there is an error in calculations - see video description)](https://www.youtube.com/watch?v=ji3SfClm8TU) - - [ ] 32 bit: [IEEE754 32-bit floating point binary (video)](https://www.youtube.com/watch?v=50ZYcZebIec) - ### Unicode - [ ] [The Absolute Minimum Every Software Developer Absolutely, Positively Must Know About Unicode and Character Sets]( http://www.joelonsoftware.com/articles/Unicode.html) @@ -1093,9 +1158,9 @@ Graphs can be used to represent many problems in computer science, so this secti - The first half is enough. - ### Networking - - **if you have networking experience or want to be a reliability engineer or operations engineer, expect questions** - - otherwise, this is just good to know - - [ ] [Khan Academy](https://www.khanacademy.org/computing/computer-science/internet-intro) + - **If you have networking experience or want to be a reliability engineer or operations engineer, expect questions** + - Otherwise, this is just good to know + - [ ] [Khan Academy](https://www.khanacademy.org/computing/code-org/computers-and-the-internet) - [ ] [UDP and TCP: Comparison of Transport Protocols (video)](https://www.youtube.com/watch?v=Vdc8TCESIg8) - [ ] [TCP/IP and the OSI Model Explained! (video)](https://www.youtube.com/watch?v=e5DEVa9eSN0) - [ ] [Packet Transmission across the Internet. Networking & TCP/IP tutorial. (video)](https://www.youtube.com/watch?v=nomyRJehhnM) @@ -1109,296 +1174,110 @@ Graphs can be used to represent many problems in computer science, so this secti - [ ] [Java - Sockets - Introduction (video)](https://www.youtube.com/watch?v=6G_W54zuadg&t=6s) - [ ] [Socket Programming (video)](https://www.youtube.com/watch?v=G75vN2mnJeQ) -## System Design, Scalability, Data Handling - -**You can expect system design questions if you have 4+ years of experience.** - -- Scalability and System Design are very large topics with many topics and resources, since - there is a lot to consider when designing a software/hardware system that can scale. - Expect to spend quite a bit of time on this. -- Considerations: - - scalability - - Distill large data sets to single values - - Transform one data set to another - - Handling obscenely large amounts of data - - system design - - features sets - - interfaces - - class hierarchies - - designing a system under certain constraints - - simplicity and robustness - - tradeoffs - - performance analysis and optimization -- [ ] **START HERE**: [The System Design Primer](https://github.com/donnemartin/system-design-primer) -- [ ] [System Design from HiredInTech](http://www.hiredintech.com/system-design/) -- [ ] [How Do I Prepare To Answer Design Questions In A Technical Inverview?](https://www.quora.com/How-do-I-prepare-to-answer-design-questions-in-a-technical-interview?redirected_qid=1500023) -- [ ] [8 Things You Need to Know Before a System Design Interview](http://blog.gainlo.co/index.php/2015/10/22/8-things-you-need-to-know-before-system-design-interviews/) -- [ ] [Algorithm design](http://www.hiredintech.com/algorithm-design/) -- [ ] [Database Normalization - 1NF, 2NF, 3NF and 4NF (video)](https://www.youtube.com/watch?v=UrYLYV7WSHM) -- [ ] [System Design Interview](https://github.com/checkcheckzz/system-design-interview) - There are a lot of resources in this one. Look through the articles and examples. I put some of them below. -- [ ] [How to ace a systems design interview](http://www.palantir.com/2011/10/how-to-rock-a-systems-design-interview/) -- [ ] [Numbers Everyone Should Know](http://everythingisdata.wordpress.com/2009/10/17/numbers-everyone-should-know/) -- [ ] [How long does it take to make a context switch?](http://blog.tsunanet.net/2010/11/how-long-does-it-take-to-make-context.html) -- [ ] [Transactions Across Datacenters (video)](https://www.youtube.com/watch?v=srOgpXECblk) -- [ ] [A plain English introduction to CAP Theorem](http://ksat.me/a-plain-english-introduction-to-cap-theorem/) -- [ ] Consensus Algorithms: - - [ ] Paxos - [Paxos Agreement - Computerphile (video)](https://www.youtube.com/watch?v=s8JqcZtvnsM) - - [ ] Raft - [An Introduction to the Raft Distributed Consensus Algorithm (video)](https://www.youtube.com/watch?v=P9Ydif5_qvE) - - [ ] [Easy-to-read paper](https://raft.github.io/) - - [ ] [Infographic](http://thesecretlivesofdata.com/raft/) -- [ ] [Consistent Hashing](http://www.tom-e-white.com/2007/11/consistent-hashing.html) -- [ ] [NoSQL Patterns](http://horicky.blogspot.com/2009/11/nosql-patterns.html) -- [ ] Scalability: - - You don't need all of these. Just pick a few that interest you. - - [ ] [Great overview (video)](https://www.youtube.com/watch?v=-W9F__D3oY4) - - [ ] Short series: - - [Clones](http://www.lecloud.net/post/7295452622/scalability-for-dummies-part-1-clones) - - [Database](http://www.lecloud.net/post/7994751381/scalability-for-dummies-part-2-database) - - [Cache](http://www.lecloud.net/post/9246290032/scalability-for-dummies-part-3-cache) - - [Asynchronism](http://www.lecloud.net/post/9699762917/scalability-for-dummies-part-4-asynchronism) - - [ ] [Scalable Web Architecture and Distributed Systems](http://www.aosabook.org/en/distsys.html) - - [ ] [Fallacies of Distributed Computing Explained](https://pages.cs.wisc.edu/~zuyu/files/fallacies.pdf) - - [ ] [Pragmatic Programming Techniques](http://horicky.blogspot.com/2010/10/scalable-system-design-patterns.html) - - [extra: Google Pregel Graph Processing](http://horicky.blogspot.com/2010/07/google-pregel-graph-processing.html) - - [ ] [Jeff Dean - Building Software Systems At Google and Lessons Learned (video)](https://www.youtube.com/watch?v=modXC5IWTJI) - - [ ] [Introduction to Architecting Systems for Scale](http://lethain.com/introduction-to-architecting-systems-for-scale/) - - [ ] [Scaling mobile games to a global audience using App Engine and Cloud Datastore (video)](https://www.youtube.com/watch?v=9nWyWwY2Onc) - - [ ] [How Google Does Planet-Scale Engineering for Planet-Scale Infra (video)](https://www.youtube.com/watch?v=H4vMcD7zKM0) - - [ ] [The Importance of Algorithms](https://www.topcoder.com/community/competitive-programming/tutorials/the-importance-of-algorithms/) - - [ ] [Sharding](http://highscalability.com/blog/2009/8/6/an-unorthodox-approach-to-database-design-the-coming-of-the.html) - - [ ] [Scale at Facebook (2012), "Building for a Billion Users" (video)](https://www.youtube.com/watch?v=oodS71YtkGU) - - [ ] [Engineering for the Long Game - Astrid Atkinson Keynote(video)](https://www.youtube.com/watch?v=p0jGmgIrf_M&list=PLRXxvay_m8gqVlExPC5DG3TGWJTaBgqSA&index=4) - - [ ] [7 Years Of YouTube Scalability Lessons In 30 Minutes](http://highscalability.com/blog/2012/3/26/7-years-of-youtube-scalability-lessons-in-30-minutes.html) - - [video](https://www.youtube.com/watch?v=G-lGCC4KKok) - - [ ] [How PayPal Scaled To Billions Of Transactions Daily Using Just 8VMs](http://highscalability.com/blog/2016/8/15/how-paypal-scaled-to-billions-of-transactions-daily-using-ju.html) - - [ ] [How to Remove Duplicates in Large Datasets](https://blog.clevertap.com/how-to-remove-duplicates-in-large-datasets/) - - [ ] [A look inside Etsy's scale and engineering culture with Jon Cowie (video)](https://www.youtube.com/watch?v=3vV4YiqKm1o) - - [ ] [What Led Amazon to its Own Microservices Architecture](http://thenewstack.io/led-amazon-microservices-architecture/) - - [ ] [To Compress Or Not To Compress, That Was Uber's Question](https://eng.uber.com/trip-data-squeeze/) - - [ ] [Asyncio Tarantool Queue, Get In The Queue](http://highscalability.com/blog/2016/3/3/asyncio-tarantool-queue-get-in-the-queue.html) - - [ ] [When Should Approximate Query Processing Be Used?](http://highscalability.com/blog/2016/2/25/when-should-approximate-query-processing-be-used.html) - - [ ] [Google's Transition From Single Datacenter, To Failover, To A Native Multihomed Architecture]( http://highscalability.com/blog/2016/2/23/googles-transition-from-single-datacenter-to-failover-to-a-n.html) - - [ ] [Spanner](http://highscalability.com/blog/2012/9/24/google-spanners-most-surprising-revelation-nosql-is-out-and.html) - - [ ] [Machine Learning Driven Programming: A New Programming For A New World](http://highscalability.com/blog/2016/7/6/machine-learning-driven-programming-a-new-programming-for-a.html) - - [ ] [The Image Optimization Technology That Serves Millions Of Requests Per Day](http://highscalability.com/blog/2016/6/15/the-image-optimization-technology-that-serves-millions-of-re.html) - - [ ] [A Patreon Architecture Short](http://highscalability.com/blog/2016/2/1/a-patreon-architecture-short.html) - - [ ] [Tinder: How Does One Of The Largest Recommendation Engines Decide Who You'll See Next?](http://highscalability.com/blog/2016/1/27/tinder-how-does-one-of-the-largest-recommendation-engines-de.html) - - [ ] [Design Of A Modern Cache](http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html) - - [ ] [Live Video Streaming At Facebook Scale](http://highscalability.com/blog/2016/1/13/live-video-streaming-at-facebook-scale.html) - - [ ] [A Beginner's Guide To Scaling To 11 Million+ Users On Amazon's AWS](http://highscalability.com/blog/2016/1/11/a-beginners-guide-to-scaling-to-11-million-users-on-amazons.html) - - [ ] [How Does The Use Of Docker Effect Latency?](http://highscalability.com/blog/2015/12/16/how-does-the-use-of-docker-effect-latency.html) - - [ ] [A 360 Degree View Of The Entire Netflix Stack](http://highscalability.com/blog/2015/11/9/a-360-degree-view-of-the-entire-netflix-stack.html) - - [ ] [Latency Is Everywhere And It Costs You Sales - How To Crush It](http://highscalability.com/latency-everywhere-and-it-costs-you-sales-how-crush-it) - - [ ] [Serverless (very long, just need the gist)](http://martinfowler.com/articles/serverless.html) - - [ ] [What Powers Instagram: Hundreds of Instances, Dozens of Technologies](http://instagram-engineering.tumblr.com/post/13649370142/what-powers-instagram-hundreds-of-instances) - - [ ] [Cinchcast Architecture - Producing 1,500 Hours Of Audio Every Day](http://highscalability.com/blog/2012/7/16/cinchcast-architecture-producing-1500-hours-of-audio-every-d.html) - - [ ] [Justin.Tv's Live Video Broadcasting Architecture](http://highscalability.com/blog/2010/3/16/justintvs-live-video-broadcasting-architecture.html) - - [ ] [Playfish's Social Gaming Architecture - 50 Million Monthly Users And Growing](http://highscalability.com/blog/2010/9/21/playfishs-social-gaming-architecture-50-million-monthly-user.html) - - [ ] [TripAdvisor Architecture - 40M Visitors, 200M Dynamic Page Views, 30TB Data](http://highscalability.com/blog/2011/6/27/tripadvisor-architecture-40m-visitors-200m-dynamic-page-view.html) - - [ ] [PlentyOfFish Architecture](http://highscalability.com/plentyoffish-architecture) - - [ ] [Salesforce Architecture - How They Handle 1.3 Billion Transactions A Day](http://highscalability.com/blog/2013/9/23/salesforce-architecture-how-they-handle-13-billion-transacti.html) - - [ ] [ESPN's Architecture At Scale - Operating At 100,000 Duh Nuh Nuhs Per Second](http://highscalability.com/blog/2013/11/4/espns-architecture-at-scale-operating-at-100000-duh-nuh-nuhs.html) - - [ ] See "Messaging, Serialization, and Queueing Systems" way below for info on some of the technologies that can glue services together - - [ ] Twitter: - - [O'Reilly MySQL CE 2011: Jeremy Cole, "Big and Small Data at @Twitter" (video)](https://www.youtube.com/watch?v=5cKTP36HVgI) - - [Timelines at Scale](https://www.infoq.com/presentations/Twitter-Timeline-Scalability) - - For even more, see "Mining Massive Datasets" video series in the [Video Series](#video-series) section. -- [ ] Practicing the system design process: Here are some ideas to try working through on paper, each with some documentation on how it was handled in the real world: - - review: [The System Design Primer](https://github.com/donnemartin/system-design-primer) - - [System Design from HiredInTech](http://www.hiredintech.com/system-design/) - - [cheat sheet](https://github.com/jwasham/coding-interview-university/blob/master/extras/cheat%20sheets/system-design.pdf) - - flow: - 1. Understand the problem and scope: - - define the use cases, with interviewer's help - - suggest additional features - - remove items that interviewer deems out of scope - - assume high availability is required, add as a use case - 2. Think about constraints: - - ask how many requests per month - - ask how many requests per second (they may volunteer it or make you do the math) - - estimate reads vs. writes percentage - - keep 80/20 rule in mind when estimating - - how much data written per second - - total storage required over 5 years - - how much data read per second - 3. Abstract design: - - layers (service, data, caching) - - infrastructure: load balancing, messaging - - rough overview of any key algorithm that drives the service - - consider bottlenecks and determine solutions - - Exercises: - - [Design a CDN network: old article](http://repository.cmu.edu/cgi/viewcontent.cgi?article=2112&context=compsci) - - [Design a random unique ID generation system](https://blog.twitter.com/2010/announcing-snowflake) - - [Design an online multiplayer card game](http://www.indieflashblog.com/how-to-create-an-asynchronous-multiplayer-game.html) - - [Design a key-value database](http://www.slideshare.net/dvirsky/introduction-to-redis) - - [Design a picture sharing system](http://highscalability.com/blog/2011/12/6/instagram-architecture-14-million-users-terabytes-of-photos.html) - - [Design a recommendation system](http://ijcai13.org/files/tutorial_slides/td3.pdf) - - [Design a URL-shortener system: copied from above](http://www.hiredintech.com/system-design/the-system-design-process/) - - [Design a cache system](https://www.adayinthelifeof.nl/2011/02/06/memcache-internals/) - --- -## Final Review +## حتمی جائزہ - This section will have shorter videos that you can watch pretty quickly to review most of the important concepts. - It's nice if you want a refresher often. + اس سیکشن میں چھوٹی ویڈیوز ہوں گی جنہیں آپ زیادہ تر اہم تصورات کا جائزہ لینے کے لیے بہت تیزی سے دیکھ سکتے ہیں۔ + اگر آپ اکثر ریفریشر چاہتے ہیں تو یہ اچھا ہے۔ -- [ ] Series of 2-3 minutes short subject videos (23 videos) - - [Videos](https://www.youtube.com/watch?v=r4r1DZcx1cM&list=PLmVb1OknmNJuC5POdcDv5oCS7_OUkDgpj&index=22) -- [ ] Series of 2-5 minutes short subject videos - Michael Sambol (40 videos): - - [Videos](https://www.youtube.com/channel/UCzDJwLWoYCUQowF_nG3m5OQ) +- [ ] 2-3 منٹ کی مختصر سبجیکٹ ویڈیوز کی سیریز (23 ویڈیوز) + - [ویڈیوز](https://www.youtube.com/watch?v=r4r1DZcx1cM&list=PLmVb1OknmNJuC5POdcDv5oCS7_OUkDgpj&index=22) +- [ ] 2-5 منٹ کی مختصر موضوع ویڈیوز کی سیریز - مائیکل سمبول (38 ویڈیوز): + - [ویڈیوز](https://www.youtube.com/channel/UCzDJwLWoYCUQowF_nG3m5OQ) - [ ] [Sedgewick Videos - Algorithms I](https://www.coursera.org/learn/algorithms-part1) - [ ] [Sedgewick Videos - Algorithms II](https://www.coursera.org/learn/algorithms-part2) --- -## Coding Question Practice +## اپنے ریزیومے کو اپ ڈیٹ کریں -Now that you know all the computer science topics above, it's time to practice answering coding problems. +- درج کتابوں میں ریزیومے کی تیاری کی معلومات دیکھیں: +- "کریکنگ دی کوڈنگ انٹرویو" اور "پروگرامنگ انٹرویوز بے نقاب" +- ["This Is What A GOOD Resume Should Look Like" by Gayle McDowell (author of Cracking the Coding Interview)](https://www.careercup.com/resume), + - مصنف کی طرف سے نوٹ: "یہ یونائیٹڈ سٹیٹس امریکا فوکسڈ ریزیومے کے لیے ہے۔ ہندوستان اور دیگر ممالک کے لیے سی وی کی توقعات مختلف ہیں، حالانکہ بہت سے پوائنٹس ایک جیسے ہوں گے۔" +- ["Step-by-step resume guide" by Tech Interview Handbook](https://www.techinterviewhandbook.org/resume/guide) + - اپنے ریزیومے کو شروع سے ترتیب دینے، موثر ریزیومے کا مواد لکھنے، اسے بہتر بنانے اور اپنے ریزیومے کی جانچ کرنے کے طریقے کے بارے میں تفصیلی گائیڈ -**Coding question practice is not about memorizing answers to programming problems.** +## انٹرویو کا عمل اور عام انٹرویو کی تیاری -Why you need to practice doing programming problems: -- problem recognition, and where the right data structures and algorithms fit in -- gathering requirements for the problem -- talking your way through the problem like you will in the interview -- coding on a whiteboard or paper, not a computer -- coming up with time and space complexity for your solutions -- testing your solutions - -There is a great intro for methodical, communicative problem solving in an interview. You'll get this from the programming -interview books, too, but I found this outstanding: -[Algorithm design canvas](http://www.hiredintech.com/algorithm-design/) - -No whiteboard at home? That makes sense. I'm a weirdo and have a big whiteboard. Instead of a whiteboard, pick up a -large drawing pad from an art store. You can sit on the couch and practice. This is my "sofa whiteboard". -I added the pen in the photo for scale. If you use a pen, you'll wish you could erase. Gets messy quick. I use a pencil -and eraser. - -![my sofa whiteboard](https://d3j2pkmjtin6ou.cloudfront.net/art_board_sm_2.jpg) - -Supplemental: - -- [Mathematics for Topcoders](https://www.topcoder.com/community/competitive-programming/tutorials/mathematics-for-topcoders/) -- [Dynamic Programming – From Novice to Advanced](https://www.topcoder.com/community/competitive-programming/tutorials/dynamic-programming-from-novice-to-advanced/) -- [MIT Interview Materials](https://web.archive.org/web/20160906124824/http://courses.csail.mit.edu/iap/interview/materials.php) - -**Read and Do Programming Problems (in this order):** - -- [ ] [Programming Interviews Exposed: Secrets to Landing Your Next Job, 2nd Edition](http://www.wiley.com/WileyCDA/WileyTitle/productCd-047012167X.html) - - answers in C, C++ and Java -- [ ] [Cracking the Coding Interview, 6th Edition](http://www.amazon.com/Cracking-Coding-Interview-6th-Programming/dp/0984782850/) - - answers in Java - -See [Book List above](#book-list) - - -## Coding exercises/challenges - -Once you've learned your brains out, put those brains to work. -Take coding challenges every day, as many as you can. - -- [How to Find a Solution](https://www.topcoder.com/community/competitive-programming/tutorials/how-to-find-a-solution/) -- [How to Dissect a Topcoder Problem Statement](https://www.topcoder.com/community/competitive-programming/tutorials/how-to-dissect-a-topcoder-problem-statement/) - -Coding Interview Question Videos: -- [IDeserve (88 videos)](https://www.youtube.com/watch?v=NBcqBddFbZw&list=PLamzFoFxwoNjPfxzaWqs7cZGsPYy0x_gI) -- [Tushar Roy (5 playlists)](https://www.youtube.com/user/tusharroy2525/playlists?shelf_id=2&view=50&sort=dd) - - Super for walkthroughs of problem solutions. -- [Nick White - LeetCode Solutions (187 Videos)](https://www.youtube.com/playlist?list=PLU_sdQYzUj2keVENTP0a5rdykRSgg9Wp-) - - Good explanations of solution and the code. - - You can watch several in a short time. -- [FisherCoder - LeetCode Solutions](https://youtube.com/FisherCoder) - -Challenge sites: -- [LeetCode](https://leetcode.com/) - - My favorite coding problem site. It's worth the subscription money for the 1-2 months you'll likely be preparing. - - [LeetCode solutions from FisherCoder](https://github.com/fishercoder1534/Leetcode) - - See Nick White Videos above for short code-throughs -- [HackerRank](https://www.hackerrank.com/) -- [TopCoder](https://www.topcoder.com/) -- [InterviewCake](https://www.interviewcake.com/) -- [Geeks for Geeks](http://www.geeksforgeeks.org/) -- [InterviewBit](https://www.interviewbit.com/invite/icjf) -- [Project Euler (math-focused)](https://projecteuler.net/index.php?section=problems) - -Language-learning sites, with challenges: -- [Codewars](http://www.codewars.com) -- [Codility](https://codility.com/programmers/) -- [HackerEarth](https://www.hackerearth.com/) -- [Sphere Online Judge (spoj)](http://www.spoj.com/) -- [Codechef](https://www.codechef.com/) - -Challenge repos: -- [Interactive Coding Interview Challenges in Python](https://github.com/donnemartin/interactive-coding-challenges) +- [ ] [How to Pass the Engineering Interview in 2021](https://davidbyttow.medium.com/how-to-pass-the-engineering-interview-in-2021-45f1b389a1) +- [ ] [Demystifying Tech Recruiting](https://www.youtube.com/watch?v=N233T0epWTs) +- [ ] How to Get a Job at the Big 4: + - [ ] [How to Get a Job at the Big 4 - Amazon, Facebook, Google & Microsoft (video)](https://www.youtube.com/watch?v=YJZCUhxNCv8) + - [ ] [How to Get a Job at the Big 4.1 (Follow-up video)](https://www.youtube.com/watch?v=6790FVXWBw8&feature=youtu.be) +- [ ] Cracking The Coding Interview Set 1: + - [ ] [Gayle L McDowell - Cracking The Coding Interview (video)](https://www.youtube.com/watch?v=rEJzOhC5ZtQ) + - [ ] [Cracking the Coding Interview with Author Gayle Laakmann McDowell (video)](https://www.youtube.com/watch?v=aClxtDcdpsQ) +- [ ] Cracking the Facebook Coding Interview: + - [ ] [The Approach](https://www.youtube.com/watch?v=wCl9kvQGHPI) + - [ ] [Problem Walkthrough](https://www.youtube.com/watch?v=4UWDyJq8jZg) +- Prep Courses: + - [Python for Data Structures, Algorithms, and Interviews (paid course)](https://www.udemy.com/python-for-data-structures-algorithms-and-interviews/): + - A Python centric interview prep course which covers data structures, algorithms, mock interviews and much more. + - [Intro to Data Structures and Algorithms using Python (Udacity free course)](https://www.udacity.com/course/data-structures-and-algorithms-in-python--ud513): + - A free Python centric data structures and algorithms course. + - [Data Structures and Algorithms Nanodegree! (Udacity paid Nanodegree)](https://www.udacity.com/course/data-structures-and-algorithms-nanodegree--nd256): + - Get hands-on practice with over 100 data structures and algorithm exercises and guidance from a dedicated mentor to help prepare you for interviews and on-the-job scenarios. + - [Grokking the Behavioral Interview (Educative free course)](https://www.educative.io/courses/grokking-the-behavioral-interview): + - Many times, it’s not your technical competency that holds you back from landing your dream job, it’s how you perform on the behavioral interview. + - [AlgoMonster (paid course with free content)](https://algo.monster/?utm_campaign=jwasham&utm_medium=referral&utm_content=coding-interview-university&utm_source=github): + - The crash course for LeetCode. Covers all the patterns condensed from thousands of questions. Mock Interviews: -- [Gainlo.co: Mock interviewers from big companies](http://www.gainlo.co/#!/) - I used this and it helped me relax for the phone screen and on-site interview. -- [Pramp: Mock interviews from/with peers](https://www.pramp.com/) - peer-to-peer model of practice interviews -- [Refdash: Mock interviews and expedited interviews](https://refdash.com/) - also help candidates fast track by skipping multiple interviews with tech companies. +- [Gainlo.co: Mock interviewers from big companies](http://www.gainlo.co/#!/) - میں نے اسے استعمال کیا اور اس نے مجھے فون اسکرین اور آن سائٹ انٹرویو کے لیے آرام دہ رہنے میں مدد کی +- [Pramp: Mock interviews from/with peers](https://www.pramp.com/) - پریکٹس انٹرویوز کا ہم مرتبہ ماڈل +- [interviewing.io: Practice mock interview with senior engineers](https://interviewing.io) - FAANG کے سینئر انجینئرز کے ساتھ الگورتھم/سسٹم ڈیزائن انٹرویوز، گمنام طور پر +## اپنے انٹرویو لینے والے کی طرح سوچیں۔ -## Once you're closer to the interview +انٹرویو کے تقریباً 20 سوالات کے بارے میں سوچیں جو آپ کو نیچے دیے گئے آئٹمز کی لائنوں کے ساتھ ملیں گے۔ ہر ایک کے لیے کم از کم ایک جواب دیں۔ +ایک کہانی رکھیں، نہ کہ صرف ڈیٹا، کسی ایسی چیز کے بارے میں جو آپ نے حاصل کی ہے۔ -- Cracking The Coding Interview Set 2 (videos): - - [Cracking The Code Interview](https://www.youtube.com/watch?v=4NIb9l3imAo) - - [Cracking the Coding Interview - Fullstack Speaker Series](https://www.youtube.com/watch?v=Eg5-tdAwclo) +- آپ کو یہ نوکری کیوں چاہیے؟ +- آپ نے کون سا مشکل مسئلہ حل کیا ہے؟ +- سب سے بڑے چیلنجز کا سامنا؟ +- بہترین/بدترین ڈیزائن جو آپ نے دیکھے ہیں؟ +- موجودہ مصنوعات کو بہتر بنانے کے خیالات +- آپ ایک فرد کے طور پر اور ایک ٹیم کے حصے کے طور پر بہترین کام کیسے کرتے ہیں؟ +- آپ کی کونسی مہارت یا تجربات اس کردار میں اثاثہ ہوں گے اور کیوں؟ +- آپ کو کس چیز میں سب سے زیادہ مزہ آیا [job x / project y]؟ +- سب سے بڑا چیلنج جس کا آپ نے سامنا کیا؟ +- سب سے مشکل بگ جس کا آپ نے سامنا کیا؟ +- آپ نے اس میں کیا سیکھا؟ [job x / project y]؟ +- آپ اپنے پروجیکٹ میں کیا بہتر کرتے؟ -## Your Resume +## انٹرویو لینے والے کے لیے سوالات -- See Resume prep items in Cracking The Coding Interview and back of Programming Interviews Exposed +میرے کچھ (ہو سکتا ہے کہ میں پہلے سے ہی جوابات جانتا ہوں، لیکن ان کی رائے یا ٹیم کے نقطہ نظر کو سمجھنے کے لیے): +- آپ کی ٹیم کتنی بڑی ہے؟ +- آپ کا دیو سائیکل کیا ہے؟ کیا آپ واٹرفال/سپرنٹ/اجائیل کرتے ہیں؟ +- کیا ڈیڈ لائن پر جلدی کرنا عام ہے؟ یا لچک ہے؟ +- آپ کی ٹیم میں فیصلے کیسے ہوتے ہیں؟ +- آپ فی ہفتہ کتنی میٹنگز کرتے ہیں؟ +- کیا آپ محسوس کرتے ہیں کہ آپ کے کام کا ماحول آپ کو توجہ مرکوز کرنے میں مدد کرتا ہے؟ +- کس پر کام کر رہے ہو؟ +- آپ کو اس کے بارے میں کیا پسند ہے؟ +- کام کی زندگی کیسی ہے؟ +- کام/زندگی کا توازن کیسا ہے؟ -## Be thinking of for when the interview comes +## ایک بار جب آپ کو نوکری مل جائے گی -Think of about 20 interview questions you'll get, along with the lines of the items below. Have 2-3 answers for each. -Have a story, not just data, about something you accomplished. +مبارک ہو! -- Why do you want this job? -- What's a tough problem you've solved? -- Biggest challenges faced? -- Best/worst designs seen? -- Ideas for improving an existing product. -- How do you work best, as an individual and as part of a team? -- Which of your skills or experiences would be assets in the role and why? -- What did you most enjoy at [job x / project y]? -- What was the biggest challenge you faced at [job x / project y]? -- What was the hardest bug you faced at [job x / project y]? -- What did you learn at [job x / project y]? -- What would you have done better at [job x / project y]? +سیکھتے رہیں۔ -## Have questions for the interviewer - - Some of mine (I already may know answer to but want their opinion or team perspective): - -- How large is your team? -- What does your dev cycle look like? Do you do waterfall/sprints/agile? -- Are rushes to deadlines common? Or is there flexibility? -- How are decisions made in your team? -- How many meetings do you have per week? -- Do you feel your work environment helps you concentrate? -- What are you working on? -- What do you like about it? -- What is the work life like? -- How is work/life balance? - -## Once You've Got The Job - -Congratulations! - -Keep learning. - -You're never really done. +ابھی بھی بہت کچھ کرنا باقی ہے. --- ***************************************************************************************************** ***************************************************************************************************** - Everything below this point is optional. - By studying these, you'll get greater exposure to more CS concepts, and will be better prepared for - any software engineering job. You'll be a much more well-rounded software engineer. - + اس نقطہ کے نیچے ہر چیز اختیاری ہے۔ داخلہ سطح کے انٹرویو کے لیے اس کی ضرورت نہیں ہے۔ تاہم، ان کا مطالعہ کرنے سےآپ کمپیوٹر سائنس کے + مزید تصورات سے زیادہ روشناس ہوں گے،اور آپ کسی بھی سافٹ ویئر انجینئرنگ کے کام کے لیے بہتر طور پر تیار ہوں گے۔ آپ ایک اچھے سافٹ ویئر انجینئر بنیں گے۔ + ***************************************************************************************************** ***************************************************************************************************** @@ -1409,40 +1288,39 @@ You're never really done. These are here so you can dive into a topic you find interesting. - [The Unix Programming Environment](https://www.amazon.com/dp/013937681X) - - an oldie but a goodie + - An oldie but a goodie - [The Linux Command Line: A Complete Introduction](https://www.amazon.com/dp/1593273894/) - - a modern option + - A modern option - [TCP/IP Illustrated Series](https://en.wikipedia.org/wiki/TCP/IP_Illustrated) - [Head First Design Patterns](https://www.amazon.com/gp/product/0596007124/) - - a gentle introduction to design patterns + - A gentle introduction to design patterns - [Design Patterns: Elements of Reusable Object-Oriente​d Software](https://www.amazon.com/Design-Patterns-Elements-Reusable-Object-Oriented/dp/0201633612) - - aka the "Gang Of Four" book, or GOF - - the canonical design patterns book -- [UNIX and Linux System Administration Handbook, 5th Edition](https://www.amazon.com/UNIX-Linux-System-Administration-Handbook/dp/0134277554/) + - AKA the "Gang Of Four" book, or GOF + - The canonical design patterns book - [Algorithm Design Manual](http://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1849967202) (Skiena) - As a review and problem recognition - - The algorithm catalog portion is well beyond the scope of difficulty you'll get in an interview. + - The algorithm catalog portion is well beyond the scope of difficulty you'll get in an interview - This book has 2 parts: - - class textbook on data structures and algorithms - - pros: - - is a good review as any algorithms textbook would be - - nice stories from his experiences solving problems in industry and academia - - code examples in C - - cons: - - can be as dense or impenetrable as CLRS, and in some cases, CLRS may be a better alternative for some subjects - - chapters 7, 8, 9 can be painful to try to follow, as some items are not explained well or require more brain than I have - - don't get me wrong: I like Skiena, his teaching style, and mannerisms, but I may not be Stony Brook material. - - algorithm catalog: - - this is the real reason you buy this book. - - about to get to this part. Will update here once I've made my way through it. - - Can rent it on kindle + - Class textbook on data structures and algorithms + - Pros: + - Is a good review as any algorithms textbook would be + - Nice stories from his experiences solving problems in industry and academia + - Code examples in C + - Cons: + - Can be as dense or impenetrable as CLRS, and in some cases, CLRS may be a better alternative for some subjects + - Chapters 7, 8, 9 can be painful to try to follow, as some items are not explained well or require more brain than I have + - Don't get me wrong: I like Skiena, his teaching style, and mannerisms, but I may not be Stony Brook material + - Algorithm catalog: + - This is the real reason you buy this book. + - This book is better as an algorithm reference, and not something you read cover to cover. + - Can rent it on Kindle - Answers: - - [Solutions](http://www.algorithm.cs.sunysb.edu/algowiki/index.php/The_Algorithms_Design_Manual_(Second_Edition)) - - [Solutions](http://blog.panictank.net/category/algorithmndesignmanualsolutions/page/2/) + - [Solutions](https://web.archive.org/web/20150404194210/http://www.algorithm.cs.sunysb.edu/algowiki/index.php/The_Algorithms_Design_Manual_(Second_Edition)) - [Errata](http://www3.cs.stonybrook.edu/~skiena/algorist/book/errata) +- [Algorithm](http://jeffe.cs.illinois.edu/teaching/algorithms/) (Jeff Erickson) - [Write Great Code: Volume 1: Understanding the Machine](https://www.amazon.com/Write-Great-Code-Understanding-Machine/dp/1593270038) - - The book was published in 2004, and is somewhat outdated, but it's a terrific resource for understanding a computer in brief. - - The author invented [HLA](https://en.wikipedia.org/wiki/High_Level_Assembly), so take mentions and examples in HLA with a grain of salt. Not widely used, but decent examples of what assembly looks like. + - The book was published in 2004, and is somewhat outdated, but it's a terrific resource for understanding a computer in brief + - The author invented [HLA](https://en.wikipedia.org/wiki/High_Level_Assembly), so take mentions and examples in HLA with a grain of salt. Not widely used, but decent examples of what assembly looks like - These chapters are worth the read to give you a nice foundation: - Chapter 2 - Numeric Representation - Chapter 3 - Binary Arithmetic and Bit Operations @@ -1453,21 +1331,127 @@ You're never really done. - Chapter 9 - CPU Architecture - Chapter 10 - Instruction Set Architecture - Chapter 11 - Memory Architecture and Organization -- [Introduction to Algorithms](https://www.amazon.com/Introduction-Algorithms-3rd-MIT-Press/dp/0262033844) - - **Important:** Reading this book will only have limited value. This book is a great review of algorithms and data structures, but won't teach you how to write good code. You have to be able to code a decent solution efficiently. - - aka CLR, sometimes CLRS, because Stein was late to the game - +- [Introduction to Algorithms](https://www.amazon.com/Introduction-Algorithms-fourth-Thomas-Cormen/dp/026204630X) + - **Important:** Reading this book will only have limited value. This book is a great review of algorithms and data structures, but won't teach you how to write good code. You have to be able to code a decent solution efficiently + - AKA CLR, sometimes CLRS, because Stein was late to the game - [Computer Architecture, Sixth Edition: A Quantitative Approach](https://www.amazon.com/dp/0128119055) - For a richer, more up-to-date (2017), but longer treatment -- [Programming Pearls](http://www.amazon.com/Programming-Pearls-2nd-Jon-Bentley/dp/0201657880) - - The first couple of chapters present clever solutions to programming problems (some very old using data tape) but - that is just an intro. This a guidebook on program design and architecture. +## System Design, Scalability, Data Handling + +**اگر آپ کے پاس 4+ سال کا تجربہ ہے تو آپ سسٹم ڈیزائن کے سوالات کی توقع کر سکتے ہیں۔** + +- Scalability and System Design are very large topics with many topics and resources, since + there is a lot to consider when designing a software/hardware system that can scale. + Expect to spend quite a bit of time on this +- Considerations: + - Scalability + - Distill large data sets to single values + - Transform one data set to another + - Handling obscenely large amounts of data + - System design + - features sets + - interfaces + - class hierarchies + - designing a system under certain constraints + - simplicity and robustness + - tradeoffs + - performance analysis and optimization +- [ ] **START HERE**: [The System Design Primer](https://github.com/donnemartin/system-design-primer) +- [ ] [System Design from HiredInTech](http://www.hiredintech.com/system-design/) +- [ ] [How Do I Prepare To Answer Design Questions In A Technical Interview?](https://www.quora.com/How-do-I-prepare-to-answer-design-questions-in-a-technical-interview?redirected_qid=1500023) +- [ ] [8 Things You Need to Know Before a System Design Interview](http://blog.gainlo.co/index.php/2015/10/22/8-things-you-need-to-know-before-system-design-interviews/) +- [ ] [Database Normalization - 1NF, 2NF, 3NF and 4NF (video)](https://www.youtube.com/watch?v=UrYLYV7WSHM) +- [ ] [System Design Interview](https://github.com/checkcheckzz/system-design-interview) - There are a lot of resources in this one. Look through the articles and examples. I put some of them below +- [ ] [How to ace a systems design interview](https://web.archive.org/web/20120716060051/http://www.palantir.com/2011/10/how-to-rock-a-systems-design-interview/) +- [ ] [Numbers Everyone Should Know](http://everythingisdata.wordpress.com/2009/10/17/numbers-everyone-should-know/) +- [ ] [How long does it take to make a context switch?](http://blog.tsunanet.net/2010/11/how-long-does-it-take-to-make-context.html) +- [ ] [Transactions Across Datacenters (video)](https://www.youtube.com/watch?v=srOgpXECblk) +- [ ] [A plain English introduction to CAP Theorem](http://ksat.me/a-plain-english-introduction-to-cap-theorem) +- [ ] [MIT 6.824: Distributed Systems, Spring 2020 (20 videos)](https://www.youtube.com/watch?v=cQP8WApzIQQ&list=PLrw6a1wE39_tb2fErI4-WkMbsvGQk9_UB) +- [ ] Consensus Algorithms: + - [ ] Paxos - [Paxos Agreement - Computerphile (video)](https://www.youtube.com/watch?v=s8JqcZtvnsM) + - [ ] Raft - [An Introduction to the Raft Distributed Consensus Algorithm (video)](https://www.youtube.com/watch?v=P9Ydif5_qvE) + - [ ] [Easy-to-read paper](https://raft.github.io/) + - [ ] [Infographic](http://thesecretlivesofdata.com/raft/) +- [ ] [Consistent Hashing](http://www.tom-e-white.com/2007/11/consistent-hashing.html) +- [ ] [NoSQL Patterns](http://horicky.blogspot.com/2009/11/nosql-patterns.html) +- [ ] Scalability: + - آپ کو ان سب کی ضرورت نہیں ہے۔ صرف چند ایک منتخب کریں جو آپ کی دلچسپی رکھتے ہیں۔ + - [ ] [Great overview (video)](https://www.youtube.com/watch?v=-W9F__D3oY4) + - [ ] Short series: + - [Clones](http://www.lecloud.net/post/7295452622/scalability-for-dummies-part-1-clones) + - [Database](http://www.lecloud.net/post/7994751381/scalability-for-dummies-part-2-database) + - [Cache](http://www.lecloud.net/post/9246290032/scalability-for-dummies-part-3-cache) + - [Asynchronism](http://www.lecloud.net/post/9699762917/scalability-for-dummies-part-4-asynchronism) + - [ ] [Scalable Web Architecture and Distributed Systems](http://www.aosabook.org/en/distsys.html) + - [ ] [Fallacies of Distributed Computing Explained](https://pages.cs.wisc.edu/~zuyu/files/fallacies.pdf) + - [ ] [Jeff Dean - Building Software Systems At Google and Lessons Learned (video)](https://www.youtube.com/watch?v=modXC5IWTJI) + - [ ] [Introduction to Architecting Systems for Scale](http://lethain.com/introduction-to-architecting-systems-for-scale/) + - [ ] [Scaling mobile games to a global audience using App Engine and Cloud Datastore (video)](https://www.youtube.com/watch?v=9nWyWwY2Onc) + - [ ] [How Google Does Planet-Scale Engineering for Planet-Scale Infra (video)](https://www.youtube.com/watch?v=H4vMcD7zKM0) + - [ ] [The Importance of Algorithms](https://www.topcoder.com/thrive/articles/The%20Importance%20of%20Algorithms) + - [ ] [Sharding](http://highscalability.com/blog/2009/8/6/an-unorthodox-approach-to-database-design-the-coming-of-the.html) + - [ ] [Engineering for the Long Game - Astrid Atkinson Keynote(video)](https://www.youtube.com/watch?v=p0jGmgIrf_M&list=PLRXxvay_m8gqVlExPC5DG3TGWJTaBgqSA&index=4) + - [ ] [7 Years Of YouTube Scalability Lessons In 30 Minutes](http://highscalability.com/blog/2012/3/26/7-years-of-youtube-scalability-lessons-in-30-minutes.html) + - [video](https://www.youtube.com/watch?v=G-lGCC4KKok) + - [ ] [How PayPal Scaled To Billions Of Transactions Daily Using Just 8VMs](http://highscalability.com/blog/2016/8/15/how-paypal-scaled-to-billions-of-transactions-daily-using-ju.html) + - [ ] [How to Remove Duplicates in Large Datasets](https://blog.clevertap.com/how-to-remove-duplicates-in-large-datasets/) + - [ ] [A look inside Etsy's scale and engineering culture with Jon Cowie (video)](https://www.youtube.com/watch?v=3vV4YiqKm1o) + - [ ] [What Led Amazon to its Own Microservices Architecture](http://thenewstack.io/led-amazon-microservices-architecture/) + - [ ] [To Compress Or Not To Compress, That Was Uber's Question](https://eng.uber.com/trip-data-squeeze/) + - [ ] [When Should Approximate Query Processing Be Used?](http://highscalability.com/blog/2016/2/25/when-should-approximate-query-processing-be-used.html) + - [ ] [Google's Transition From Single Datacenter, To Failover, To A Native Multihomed Architecture]( http://highscalability.com/blog/2016/2/23/googles-transition-from-single-datacenter-to-failover-to-a-n.html) + - [ ] [The Image Optimization Technology That Serves Millions Of Requests Per Day](http://highscalability.com/blog/2016/6/15/the-image-optimization-technology-that-serves-millions-of-re.html) + - [ ] [A Patreon Architecture Short](http://highscalability.com/blog/2016/2/1/a-patreon-architecture-short.html) + - [ ] [Tinder: How Does One Of The Largest Recommendation Engines Decide Who You'll See Next?](http://highscalability.com/blog/2016/1/27/tinder-how-does-one-of-the-largest-recommendation-engines-de.html) + - [ ] [Design Of A Modern Cache](http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html) + - [ ] [Live Video Streaming At Facebook Scale](http://highscalability.com/blog/2016/1/13/live-video-streaming-at-facebook-scale.html) + - [ ] [A Beginner's Guide To Scaling To 11 Million+ Users On Amazon's AWS](http://highscalability.com/blog/2016/1/11/a-beginners-guide-to-scaling-to-11-million-users-on-amazons.html) + - [ ] [A 360 Degree View Of The Entire Netflix Stack](http://highscalability.com/blog/2015/11/9/a-360-degree-view-of-the-entire-netflix-stack.html) + - [ ] [Latency Is Everywhere And It Costs You Sales - How To Crush It](http://highscalability.com/latency-everywhere-and-it-costs-you-sales-how-crush-it) + - [ ] [What Powers Instagram: Hundreds of Instances, Dozens of Technologies](http://instagram-engineering.tumblr.com/post/13649370142/what-powers-instagram-hundreds-of-instances) + - [ ] [Salesforce Architecture - How They Handle 1.3 Billion Transactions A Day](http://highscalability.com/blog/2013/9/23/salesforce-architecture-how-they-handle-13-billion-transacti.html) + - [ ] [ESPN's Architecture At Scale - Operating At 100,000 Duh Nuh Nuhs Per Second](http://highscalability.com/blog/2013/11/4/espns-architecture-at-scale-operating-at-100000-duh-nuh-nuhs.html) + - [ ] See "Messaging, Serialization, and Queueing Systems" way below for info on some of the technologies that can glue services together + - [ ] Twitter: + - [O'Reilly MySQL CE 2011: Jeremy Cole, "Big and Small Data at @Twitter" (video)](https://www.youtube.com/watch?v=5cKTP36HVgI) + - [Timelines at Scale](https://www.infoq.com/presentations/Twitter-Timeline-Scalability) + - For even more, see "Mining Massive Datasets" video series in the [Video Series](#video-series) section +- [ ] Practicing the system design process: Here are some ideas to try working through on paper, each with some documentation on how it was handled in the real world: + - review: [The System Design Primer](https://github.com/donnemartin/system-design-primer) + - [System Design from HiredInTech](http://www.hiredintech.com/system-design/) + - [cheat sheet](https://github.com/jwasham/coding-interview-university/blob/main/extras/cheat%20sheets/system-design.pdf) + - flow: + 1. سوال اور سوال کے دائرہ کار کو سمجھیں: + - انٹرویو لینے والے کی مدد سے استعمال کے معاملات کی وضاحت کریں + - اضافی خصوصیات تجویز کریں + - ایسے آئٹمز کو ہٹا دیں جن کو انٹرویو لینے والے دائرہ کار سے باہر سمجھتے ہیں + - فرض کریں کہ اعلی دستیابی کی ضرورت ہے، اضرورت کے طور پر شامل کریں + 2. پابندیوں کے بارے میں سوچو: + - پوچھیں کہ ماہانہ کتنی درخواستیں ہیں + - پوچھیں کہ فی سیکنڈ کتنی درخواستیں ہیں (وہ اسے رضاکارانہ طور پر دے سکتے ہیں یا آپ کو حساب کتاب کرنے پر مجبور کر سکتے ہیں) + - تخمینہ پڑھنا بمقابلہ لکھنا فیصد + - تخمینہ لگاتے وقت 80/20 اصول کو ذہن میں رکھیں + - فی سیکنڈ میں کتنا ڈیٹا لکھا جاتا ہے + - 5 سالوں میں کل ذخیرہ درکار ہے + - فی سیکنڈ کتنا ڈیٹا پڑھتا ہے + 3. ڈیزائن کاخلاصہ: + - پرتیں (سروس، ڈیٹا، کیشنگ) + - انفراسٹرکچر: بوجھ میں توازن، پیغام رسانی + - سروس کو چلانے والے کسی بھی کلیدی الگورتھم کا کچا جائزہ + - رکاوٹوں پر غور کریں اور حل کا تعین کریں + - Exercises: + - [Design a random unique ID generation system](https://blog.twitter.com/2010/announcing-snowflake) + - [Design a key-value database](http://www.slideshare.net/dvirsky/introduction-to-redis) + - [Design a picture sharing system](http://highscalability.com/blog/2011/12/6/instagram-architecture-14-million-users-terabytes-of-photos.html) + - [Design a recommendation system](http://ijcai13.org/files/tutorial_slides/td3.pdf) + - [Design a URL-shortener system: copied from above](http://www.hiredintech.com/system-design/the-system-design-process/) + - [Design a cache system](https://web.archive.org/web/20220217064329/https://adayinthelifeof.nl/2011/02/06/memcache-internals/) ## Additional Learning - - I added them to help you become a well-rounded software engineer, and to be aware of certain - technologies and algorithms, so you'll have a bigger toolbox. + + میں نے انہیں شامل کیا تاکہ آپ کو ایک بہترین سافٹ ویئر انجینئر بننے میں مدد ملے، اور کچھ ٹیکنالوجیز اور الگورتھم سے آگاہی ہو، تاکہ آپ کے پاس ایک بڑا ٹول باکس ہو۔ - ### Compilers - [How a Compiler Works in ~1 minute (video)](https://www.youtube.com/watch?v=IhC7sdYe-Jg) @@ -1494,6 +1478,8 @@ You're never really done. - [Emacs Tutorial (Beginners) -Part 3- Expressions, Statements, ~/.emacs file and packages](https://www.youtube.com/watch?v=paSgzPso-yc) - [Evil Mode: Or, How I Learned to Stop Worrying and Love Emacs (video)](https://www.youtube.com/watch?v=JWD1Fpdd4Pc) - [Writing C Programs With Emacs](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Writing_C_programs_with_Emacs) + - [The Absolute Beginner's Guide to Emacs (video by David Wilson)](https://www.youtube.com/watch?v=48JlgiBpw_I&t=0s) + - [The Absolute Beginner's Guide to Emacs (notes by David Wilson)](https://systemcrafters.net/emacs-essentials/absolute-beginners-guide-to-emacs/) - ### Unix command line tools - I filled in the list below from good tools. @@ -1511,11 +1497,11 @@ You're never really done. - ### Information theory (videos) - [Khan Academy](https://www.khanacademy.org/computing/computer-science/informationtheory) - - more about Markov processes: + - More about Markov processes: - [Core Markov Text Generation](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/waxgx/core-markov-text-generation) - [Core Implementing Markov Text Generation](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/gZhiC/core-implementing-markov-text-generation) - [Project = Markov Text Generation Walk Through](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/EUjrq/project-markov-text-generation-walk-through) - - See more in MIT 6.050J Information and Entropy series below. + - See more in MIT 6.050J Information and Entropy series below - ### Parity & Hamming Code (videos) - [Intro](https://www.youtube.com/watch?v=q-3BctoUpHE) @@ -1526,19 +1512,19 @@ You're never really done. - [Error Checking](https://www.youtube.com/watch?v=wbH2VxzmoZk) - ### Entropy - - also see videos below - - make sure to watch information theory videos first + - نیچے دی گئی ویڈیوز بھی دیکھیں + - پہلے انفارمیشن تھیوری کی ویڈیوز ضرور دیکھیں - [Information Theory, Claude Shannon, Entropy, Redundancy, Data Compression & Bits (video)](https://youtu.be/JnJq3Py0dyM?t=176) - ### Cryptography - - also see videos below - - make sure to watch information theory videos first + - نیچے دی گئی ویڈیوز بھی دیکھیں + - پہلے انفارمیشن تھیوری کی ویڈیوز ضرور دیکھیں - [Khan Academy Series](https://www.khanacademy.org/computing/computer-science/cryptography) - [Cryptography: Hash Functions](https://www.youtube.com/watch?v=KqqOXndnvic&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=30) - [Cryptography: Encryption](https://www.youtube.com/watch?v=9TNI2wHmaeI&index=31&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) - ### Compression - - make sure to watch information theory videos first + - پہلے انفارمیشن تھیوری کی ویڈیوز ضرور دیکھیں - Computerphile (videos): - [Compression](https://www.youtube.com/watch?v=Lto-ajuqW3w) - [Entropy in Compression](https://www.youtube.com/watch?v=M5c_RFKVkko) @@ -1597,7 +1583,6 @@ You're never really done. - ### A* - [A Search Algorithm](https://en.wikipedia.org/wiki/A*_search_algorithm) - - [A* Pathfinding Tutorial (video)](https://www.youtube.com/watch?v=KNXfSOx4eEE) - [A* Pathfinding (E01: algorithm explanation) (video)](https://www.youtube.com/watch?v=-L-WgKMFuhE) - ### Fast Fourier Transform @@ -1618,8 +1603,8 @@ You're never really done. - [How To Count A Billion Distinct Objects Using Only 1.5KB Of Memory](http://highscalability.com/blog/2012/4/5/big-data-counting-how-to-count-a-billion-distinct-objects-us.html) - ### Locality-Sensitive Hashing - - used to determine the similarity of documents - - the opposite of MD5 or SHA which are used to determine if 2 documents/strings are exactly the same. + - Used to determine the similarity of documents + - The opposite of MD5 or SHA which are used to determine if 2 documents/strings are exactly the same - [Simhashing (hopefully) made simple](http://ferd.ca/simhashing-hopefully-made-simple.html) - ### van Emde Boas Trees @@ -1630,17 +1615,17 @@ You're never really done. - [CS 61B Lecture 39: Augmenting Data Structures](https://archive.org/details/ucberkeley_webcast_zksIj9O8_jc) - ### Balanced search trees - - Know at least one type of balanced binary tree (and know how it's implemented): + - کم از کم ایک قسم کے بیلنسڈ بائنری ٹری کو جانیں (اور جانیں کہ اسے کیسے کوڈ کیا گیا ہے): - "Among balanced search trees, AVL and 2/3 trees are now passé, and red-black trees seem to be more popular. A particularly interesting self-organizing data structure is the splay tree, which uses rotations to move any accessed key to the root." - Skiena - Of these, I chose to implement a splay tree. From what I've read, you won't implement a balanced search tree in your interview. But I wanted exposure to coding one up - and let's face it, splay trees are the bee's knees. I did read a lot of red-black tree code. - - splay tree: insert, search, delete functions + and let's face it, splay trees are the bee's knees. I did read a lot of red-black tree code + - Splay tree: insert, search, delete functions If you end up implementing red/black tree try just these: - - search and insertion functions, skipping delete - - I want to learn more about B-Tree since it's used so widely with very large data sets. + - Search and insertion functions, skipping delete + - I want to learn more about B-Tree since it's used so widely with very large data sets - [Self-balancing binary search tree](https://en.wikipedia.org/wiki/Self-balancing_binary_search_tree) - **AVL trees** @@ -1649,7 +1634,7 @@ You're never really done. The AVL tree is another structure supporting O(log n) search, insertion, and removal. It is more rigidly balanced than red–black trees, leading to slower insertion and removal but faster retrieval. This makes it attractive for data structures that may be built once and loaded without reconstruction, such as language - dictionaries (or program dictionaries, such as the opcodes of an assembler or interpreter). + dictionaries (or program dictionaries, such as the opcodes of an assembler or interpreter) - [MIT AVL Trees / AVL Sort (video)](https://www.youtube.com/watch?v=FNeL18KsWPc&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=6) - [AVL Trees (video)](https://www.coursera.org/learn/data-structures/lecture/Qq5E0/avl-trees) - [AVL Tree Implementation (video)](https://www.coursera.org/learn/data-structures/lecture/PKEBC/avl-tree-implementation) @@ -1659,14 +1644,14 @@ You're never really done. - In practice: Splay trees are typically used in the implementation of caches, memory allocators, routers, garbage collectors, data compression, ropes (replacement of string used for long text strings), in Windows NT (in the virtual memory, - networking and file system code) etc. + networking and file system code) etc - [CS 61B: Splay Trees (video)](https://archive.org/details/ucberkeley_webcast_G5QIXywcJlY) - MIT Lecture: Splay Trees: - Gets very mathy, but watch the last 10 minutes for sure. - [Video](https://www.youtube.com/watch?v=QnPl_Y6EqMo) - **Red/black trees** - - these are a translation of a 2-3 tree (see below) + - These are a translation of a 2-3 tree (see below). - In practice: Red–black trees offer worst-case guarantees for insertion time, deletion time, and search time. Not only does this make them valuable in time-sensitive applications such as real-time applications, @@ -1674,7 +1659,7 @@ You're never really done. for example, many data structures used in computational geometry can be based on red–black trees, and the Completely Fair Scheduler used in current Linux kernels uses red–black trees. In the version 8 of Java, the Collection HashMap has been modified such that instead of using a LinkedList to store identical elements with poor - hashcodes, a Red-Black tree is used. + hashcodes, a Red-Black tree is used - [Aduni - Algorithms - Lecture 4 (link jumps to starting point) (video)](https://youtu.be/1W3x0f_RmUo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3871) - [Aduni - Algorithms - Lecture 5 (video)](https://www.youtube.com/watch?v=hm2GHwyKF1o&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=5) - [Red-Black Tree](https://en.wikipedia.org/wiki/Red%E2%80%93black_tree) @@ -1706,12 +1691,12 @@ You're never really done. - [K-Ary Tree](https://en.wikipedia.org/wiki/K-ary_tree) - **B-Trees** - - fun fact: it's a mystery, but the B could stand for Boeing, Balanced, or Bayer (co-inventor) + - Fun fact: it's a mystery, but the B could stand for Boeing, Balanced, or Bayer (co-inventor). - In Practice: B-Trees are widely used in databases. Most modern filesystems use B-trees (or Variants). In addition to its use in databases, the B-tree is also used in filesystems to allow quick random access to an arbitrary block in a particular file. The basic problem is turning the file block i address into a disk block - (or perhaps to a cylinder-head-sector) address. + (or perhaps to a cylinder-head-sector) address - [B-Tree](https://en.wikipedia.org/wiki/B-tree) - [B-Tree Datastructure](http://btechsmartclass.com/data_structures/b-trees.html) - [Introduction to B-Trees (video)](https://www.youtube.com/watch?v=I22wEC1tTGo&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=6) @@ -1724,9 +1709,8 @@ You're never really done. - ### k-D Trees - - great for finding number of points in a rectangle or higher dimension object - - a good fit for k-nearest neighbors - - [Kd Trees (video)](https://www.youtube.com/watch?v=W94M9D_yXKk) + - Great for finding number of points in a rectangle or higher dimension object + - A good fit for k-nearest neighbors - [kNN K-d tree algorithm (video)](https://www.youtube.com/watch?v=Y4ZgLlDfKDg) - ### Skip lists @@ -1765,49 +1749,24 @@ You're never really done. - [Divide & Conquer: Convex Hull, Median Finding](https://www.youtube.com/watch?v=EzeYI7p9MjU&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=2) - ### Discrete math - - see videos below - -- ### Machine Learning - - Why ML? - - [How Google Is Remaking Itself As A Machine Learning First Company](https://backchannel.com/how-google-is-remaking-itself-as-a-machine-learning-first-company-ada63defcb70) - - [Large-Scale Deep Learning for Intelligent Computer Systems (video)](https://www.youtube.com/watch?v=QSaZGT4-6EY) - - [Deep Learning and Understandability versus Software Engineering and Verification by Peter Norvig](https://www.youtube.com/watch?v=X769cyzBNVw) - - [Google's Cloud Machine learning tools (video)](https://www.youtube.com/watch?v=Ja2hxBAwG_0) - - [Google Developers' Machine Learning Recipes (Scikit Learn & Tensorflow) (video)](https://www.youtube.com/playlist?list=PLOU2XLYxmsIIuiBfYad6rFYQU_jL2ryal) - - [Tensorflow (video)](https://www.youtube.com/watch?v=oZikw5k_2FM) - - [Tensorflow Tutorials](https://www.tensorflow.org/versions/r0.11/tutorials/index.html) - - [Practical Guide to implementing Neural Networks in Python (using Theano)](http://www.analyticsvidhya.com/blog/2016/04/neural-networks-python-theano/) - - Courses: - - [Great starter course: Machine Learning](https://www.coursera.org/learn/machine-learning) - - [videos only](https://www.youtube.com/playlist?list=PLZ9qNFMHZ-A4rycgrgOYma6zxF4BZGGPW) - - see videos 12-18 for a review of linear algebra (14 and 15 are duplicates) - - [Neural Networks for Machine Learning](https://www.coursera.org/learn/neural-networks) - - [Google's Deep Learning Nanodegree](https://www.udacity.com/course/deep-learning--ud730) - - [Google/Kaggle Machine Learning Engineer Nanodegree](https://www.udacity.com/course/machine-learning-engineer-nanodegree-by-google--nd009) - - [Self-Driving Car Engineer Nanodegree](https://www.udacity.com/drive) - - Resources: - - Books: - - [Python Machine Learning](https://www.amazon.com/Python-Machine-Learning-Sebastian-Raschka/dp/1783555130/) - - [Data Science from Scratch: First Principles with Python](https://www.amazon.com/Data-Science-Scratch-Principles-Python/dp/149190142X) - - [Introduction to Machine Learning with Python](https://www.amazon.com/Introduction-Machine-Learning-Python-Scientists/dp/1449369413/) - - [Machine Learning for Software Engineers](https://github.com/ZuzooVn/machine-learning-for-software-engineers) - - Data School: http://www.dataschool.io/ + - [Computer Science 70, 001 - Spring 2015 - Discrete Mathematics and Probability Theory](http://www.infocobuild.com/education/audio-video-courses/computer-science/cs70-spring2015-berkeley.html) + - [Discrete Mathematics by Shai Simonson (19 videos)](https://www.youtube.com/playlist?list=PLWX710qNZo_sNlSWRMVIh6kfTjolNaZ8t) + - [Discrete Mathematics By IIT Ropar NPTEL](https://nptel.ac.in/courses/106/106/106106183/) --- ## Additional Detail on Some Subjects - I added these to reinforce some ideas already presented above, but didn't want to include them - above because it's just too much. It's easy to overdo it on a subject. - You want to get hired in this century, right? + میں نے ان کو پہلے سے پیش کیے گئے کچھ خیالات کو تقویت دینے کے لیے شامل کیا تھا لیکن میں انھیں اوپر شامل نہیں کرنا چاہتا تھا کیونکہ یہ کافی سے زیادہ ہے۔ کسی ایک موضوع پر اسے زیادہ کرنا آسان ہے۔ +آپ اس صدی میں ملازمت حاصل کرنا چاہتے ہیں، کیا میں ٹھیک کہہ رہا ہوں؟ - **SOLID** - [ ] [Bob Martin SOLID Principles of Object Oriented and Agile Design (video)](https://www.youtube.com/watch?v=TMuno5RZNeE) - [ ] S - [Single Responsibility Principle](http://www.oodesign.com/single-responsibility-principle.html) | [Single responsibility to each Object](http://www.javacodegeeks.com/2011/11/solid-single-responsibility-principle.html) - [more flavor](https://docs.google.com/open?id=0ByOwmqah_nuGNHEtcU5OekdDMkk) - - [ ] O - [Open/Closed Principal](http://www.oodesign.com/open-close-principle.html) | [On production level Objects are ready for extension but not for modification](https://en.wikipedia.org/wiki/Open/closed_principle) + - [ ] O - [Open/Closed Principle](http://www.oodesign.com/open-close-principle.html) | [On production level Objects are ready for extension but not for modification](https://en.wikipedia.org/wiki/Open/closed_principle) - [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgN2M5MTkwM2EtNWFkZC00ZTI3LWFjZTUtNTFhZGZiYmUzODc1&hl=en) - - [ ] L - [Liskov Substitution Principal](http://www.oodesign.com/liskov-s-substitution-principle.html) | [Base Class and Derived class follow ‘IS A’ principal](http://stackoverflow.com/questions/56860/what-is-the-liskov-substitution-principle) + - [ ] L - [Liskov Substitution Principle](http://www.oodesign.com/liskov-s-substitution-principle.html) | [Base Class and Derived class follow ‘IS A’ Principle](http://stackoverflow.com/questions/56860/what-is-the-liskov-substitution-principle) - [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgNzAzZjA5ZmItNjU3NS00MzQ5LTkwYjMtMDJhNDU5ZTM0MTlh&hl=en) - [ ] I - [Interface segregation principle](http://www.oodesign.com/interface-segregation-principle.html) | clients should not be forced to implement interfaces they don't use - [Interface Segregation Principle in 5 minutes (video)](https://www.youtube.com/watch?v=3CtAfl7aXAQ) @@ -1826,10 +1785,10 @@ You're never really done. - [Analysis Options](https://www.coursera.org/learn/data-structures/lecture/GQQLN/analysis-optional) - **More Dynamic Programming** (videos) - - [6.006: Dynamic Programming I: Fibonacci, Shortest Paths](https://www.youtube.com/watch?v=OQ5jsbhAv_M&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=19) - - [6.006: Dynamic Programming II: Text Justification, Blackjack](https://www.youtube.com/watch?v=ENyox7kNKeY&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=20) - - [6.006: DP III: Parenthesization, Edit Distance, Knapsack](https://www.youtube.com/watch?v=ocZMDMZwhCY&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=21) - - [6.006: DP IV: Guitar Fingering, Tetris, Super Mario Bros.](https://www.youtube.com/watch?v=tp4_UXaVyx8&index=22&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) + - [6.006: Dynamic Programming I: Fibonacci, Shortest Paths](https://www.youtube.com/watch?v=r4-cftqTcdI&ab_channel=MITOpenCourseWare) + - [6.006: Dynamic Programming II: Text Justification, Blackjack](https://www.youtube.com/watch?v=KLBCUx1is2c&ab_channel=MITOpenCourseWare) + - [6.006: DP III: Parenthesization, Edit Distance, Knapsack](https://www.youtube.com/watch?v=TDo3r5M1LNo&ab_channel=MITOpenCourseWare) + - [6.006: DP IV: Guitar Fingering, Tetris, Super Mario Bros.](https://www.youtube.com/watch?v=i9OAOk0CUQE&ab_channel=MITOpenCourseWare) - [6.046: Dynamic Programming & Advanced DP](https://www.youtube.com/watch?v=Tw1k46ywN6E&index=14&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) - [6.046: Dynamic Programming: All-Pairs Shortest Paths](https://www.youtube.com/watch?v=NzgFUwOaoIw&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=15) - [6.046: Dynamic Programming (student recitation)](https://www.youtube.com/watch?v=krZI60lKPek&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=12) @@ -1852,7 +1811,7 @@ You're never really done. - **String Matching** - Rabin-Karp (videos): - - [Rabin Karps Algorithm](https://www.coursera.org/learn/data-structures/lecture/c0Qkw/rabin-karps-algorithm) + - [Rabin Karps Algorithm](https://www.coursera.org/lecture/data-structures/rabin-karps-algorithm-c0Qkw) - [Precomputing](https://www.coursera.org/learn/data-structures/lecture/nYrc8/optimization-precomputation) - [Optimization: Implementation and Analysis](https://www.coursera.org/learn/data-structures/lecture/h4ZLc/optimization-implementation-and-analysis) - [Table Doubling, Karp-Rabin](https://www.youtube.com/watch?v=BRO7mVIFt08&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=9) @@ -1872,18 +1831,18 @@ You're never really done. - Stanford lectures on sorting: - [Lecture 15 | Programming Abstractions (video)](https://www.youtube.com/watch?v=ENp00xylP7c&index=15&list=PLFE6E58F856038C69) - [Lecture 16 | Programming Abstractions (video)](https://www.youtube.com/watch?v=y4M9IVgrVKo&index=16&list=PLFE6E58F856038C69) - - Shai Simonson, [Aduni.org](http://www.aduni.org/): + - Shai Simonson: - [Algorithms - Sorting - Lecture 2 (video)](https://www.youtube.com/watch?v=odNJmw5TOEE&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=2) - [Algorithms - Sorting II - Lecture 3 (video)](https://www.youtube.com/watch?v=hj8YKFTFKEE&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=3) - Steven Skiena lectures on sorting: - - [lecture begins at 26:46 (video)](https://youtu.be/ute-pmMkyuk?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1600) - - [lecture begins at 27:40 (video)](https://www.youtube.com/watch?v=yLvp-pB8mak&index=8&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) - - [lecture begins at 35:00 (video)](https://www.youtube.com/watch?v=q7K9otnzlfE&index=9&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) - - [lecture begins at 23:50 (video)](https://www.youtube.com/watch?v=TvqIGu9Iupw&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=10) + - [CSE373 2020 - Mergesort/Quicksort (video)](https://www.youtube.com/watch?v=jUf-UQ3a0kg&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=8) + - [CSE373 2020 - Linear Sorting (video)](https://www.youtube.com/watch?v=0ksyQKmre84&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=9) + +- NAND To Tetris: [Build a Modern Computer from First Principles](https://www.coursera.org/learn/build-a-computer) ## Video Series -Sit back and enjoy. "Netflix and skill" :P +Sit back and enjoy. - [List of individual Dynamic Programming problems (each is short)](https://www.youtube.com/playlist?list=PLrmLmBdmIlpsHaNTPP_jHHDx_os9ItYXr) @@ -1893,14 +1852,7 @@ Sit back and enjoy. "Netflix and skill" :P - [Excellent - MIT Calculus Revisited: Single Variable Calculus](https://www.youtube.com/playlist?list=PL3B08AE665AB9002A) -- [Computer Science 70, 001 - Spring 2015 - Discrete Mathematics and Probability Theory](http://www.infocobuild.com/education/audio-video-courses/computer-science/cs70-spring2015-berkeley.html) - -- [Discrete Mathematics by Shai Simonson (19 videos)](https://www.youtube.com/playlist?list=PLWX710qNZo_sNlSWRMVIh6kfTjolNaZ8t) - -- [Discrete Mathematics Part 1 by Sarada Herke (5 videos)](https://www.youtube.com/playlist?list=PLGxuz-nmYlQPOc4w1Kp2MZrdqOOm4Jxeo) - -- CSE373 - Analysis of Algorithms (25 videos) - - [Skiena lectures from Algorithm Design Manual](https://www.youtube.com/watch?v=ZFjhkohHdAA&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=1) +- [Skiena lectures from Algorithm Design Manual - CSE373 2020 - Analysis of Algorithms (26 videos)](https://www.youtube.com/watch?v=22hwcnXIGgk&list=PLOtl7M3yp-DX6ic0HGT0PUX_wiNmkWkXx&index=1) - [UC Berkeley 61B (Spring 2014): Data Structures (25 videos)](https://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd) @@ -1910,8 +1862,6 @@ Sit back and enjoy. "Netflix and skill" :P - [OOSE: Software Dev Using UML and Java (21 videos)](https://www.youtube.com/playlist?list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO) -- ~~[UC Berkeley CS 152: Computer Architecture and Engineering (20 videos)](https://www.youtube.com/watch?v=UH0QYvtP7Rk&index=20&list=PLkFD6_40KJIwEiwQx1dACXwh-2Fuo32qr)~~ - - [MIT 6.004: Computation Structures (49 videos)](https://www.youtube.com/playlist?list=PLDSlqjcPpoL64CJdF0Qee5oWqGS6we_Yu) - [Carnegie Mellon - Computer Architecture Lectures (39 videos)](https://www.youtube.com/playlist?list=PL5PHm2jkkXmi5CxxI7b3JCL1TWybTDtKq) @@ -1926,7 +1876,7 @@ Sit back and enjoy. "Netflix and skill" :P - [MIT 6.046: Design and Analysis of Algorithms (34 videos)](https://www.youtube.com/watch?v=2P-yW7LQr08&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) -- [MIT 6.050J: Information and Entropy, Spring 2008 (19 videos)](https://www.youtube.com/watch?v=phxsQrZQupo&list=PL_2Bwul6T-A7OldmhGODImZL8KEVE38X7) +- [MIT 6.824: Distributed Systems, Spring 2020 (20 videos)](https://www.youtube.com/watch?v=cQP8WApzIQQ&list=PLrw6a1wE39_tb2fErI4-WkMbsvGQk9_UB) - [MIT 6.851: Advanced Data Structures (22 videos)](https://www.youtube.com/watch?v=T0yzrZL1py0&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf&index=1) @@ -1950,6 +1900,11 @@ Sit back and enjoy. "Netflix and skill" :P - [Directory of Online CS Courses](https://github.com/open-source-society/computer-science) - [Directory of CS Courses (many with online lectures)](https://github.com/prakhar1989/awesome-courses) +## Algorithms implementation + +- [Multiple Algorithms implementation by Princeton University](https://algs4.cs.princeton.edu/code) + + ## Papers - [Love classic papers?](https://www.cs.cmu.edu/~crary/819-f09/) @@ -1960,28 +1915,20 @@ Sit back and enjoy. "Netflix and skill" :P - [2004: MapReduce: Simplified Data Processing on Large Clusters]( http://static.googleusercontent.com/media/research.google.com/en//archive/mapreduce-osdi04.pdf) - mostly replaced by Cloud Dataflow? - [2006: Bigtable: A Distributed Storage System for Structured Data](https://static.googleusercontent.com/media/research.google.com/en//archive/bigtable-osdi06.pdf) - - [An Inside Look at Google BigQuery](https://cloud.google.com/files/BigQueryTechnicalWP.pdf) - [2006: The Chubby Lock Service for Loosely-Coupled Distributed Systems](https://research.google.com/archive/chubby-osdi06.pdf) - [2007: Dynamo: Amazon’s Highly Available Key-value Store](http://s3.amazonaws.com/AllThingsDistributed/sosp/amazon-dynamo-sosp2007.pdf) - The Dynamo paper kicked off the NoSQL revolution - [2007: What Every Programmer Should Know About Memory (very long, and the author encourages skipping of some sections)](https://www.akkadia.org/drepper/cpumemory.pdf) -- [2010: Dapper, a Large-Scale Distributed Systems Tracing Infrastructure](https://research.google.com/pubs/archive/36356.pdf) -- [2010: Dremel: Interactive Analysis of Web-Scale Datasets](https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/36632.pdf) -- [2012: Google's Colossus](https://www.wired.com/2012/07/google-colossus/) - - paper not available - 2012: AddressSanitizer: A Fast Address Sanity Checker: - [paper](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/37752.pdf) - [video](https://www.usenix.org/conference/atc12/technical-sessions/presentation/serebryany) - 2013: Spanner: Google’s Globally-Distributed Database: - [paper](http://static.googleusercontent.com/media/research.google.com/en//archive/spanner-osdi2012.pdf) - [video](https://www.usenix.org/node/170855) -- [2014: Machine Learning: The High-Interest Credit Card of Technical Debt](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43146.pdf) - [2015: Continuous Pipelines at Google](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43790.pdf) - [2015: High-Availability at Massive Scale: Building Google’s Data Infrastructure for Ads](https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/44686.pdf) -- [2015: TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems](http://download.tensorflow.org/paper/whitepaper2015.pdf ) - [2015: How Developers Search for Code: A Case Study](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43835.pdf) -- [2016: Borg, Omega, and Kubernetes](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/44843.pdf) - +- More papers: [1,000 papers](https://github.com/0voice/computer_expert_paper) ## LICENSE