#  कोडिंग साक्षात्कार विश्वविद्यालय
>मैने मूल रूप से इसे एक सॉफ़्टवेयर इंजीनियर बनने के लिए अध्ययन विषयों की एक छोटी सी सूची के रूप में बनाया था, लेकिन यह आज एक बड़ी सूची में बढ़ी है। इस अध्ययन योजना के माध्यम से जाने के बाद, [मुझे अमेज़ॅन पर सॉफ़्टवेयर डेवलपमेंट इंजीनियर के रूप में काम पर रखा गया है !](https://startupnextdoor.com/ive-been-acquired-by->amazon/?src=ciu) आपको संभवतः जितना मैंने किया उतना नहीं पढ़ना होगा। वैसे भी, आपको जो भी चाहिए वह यहां है
>
>यहां सूचीबद्ध आइटम आपको किसी साफ्टवेयर कंपनी के बारे में साक्षात्कार में अच्छी तरह से तैयार करेंगे, जिनमें दिग्गज, अमेज़ॅन, फेसबुक, गूगल या माइक्रोसॉफ्ट शामिल हैं।
>
>आपको शुभकामनाएं!

<div align="center">
	<hr />
    <p>
        <a href="https://github.com/sponsors/jwasham"><strong>स्पोंसर बने </strong> और कोडिंग इंटरव्यू यूनिवर्सिटी का समर्थन करे!</a>
    </p>
    <p>
        <strong>इन सब को विशेष धन्यवाद:</strong>
    </p>
    <p>
        <a href="https://oss.capital/">
            <div>
                <img src="https://d3j2pkmjtin6ou.cloudfront.net/sponsors/oss-capital.svg" width="350" alt="OSS Capital">
            </div>
            <div>
                <sup><strong>2018 में स्थापित, OSS Capital पहला और एकमात्र उद्यम पूंजी मंच है जो विशेष रूप से <br> प्रारंभिक चरण COSS (वाणिज्यिक ओपन सोर्स) स्टार्टअप संस्थापकों का समर्थन करने पर केंद्रित है।</strong></sup>
            </div>
        </a>
    </p>
    <br />
    <p>
        <a href="https://www.gitpod.io/?utm_campaign=jwasham&utm_medium=referral&utm_content=coding-interview-university&utm_source=github">
            <div>
                <img src="https://d3j2pkmjtin6ou.cloudfront.net/sponsors/gitpod-logo-light-theme.svg" width="300" alt="Gitpod">
            </div>
            <div>
                <p>
                    <strong>Dev environments built for the cloud</strong>
                </p>
            </div>
            <div>
                <sup> GitLab, GitHub, और Bitbucket के साथ मूल रूप से एकीकृत, Gitpod स्वचालित रूप से और आपकी सभी शाखाओं के लिए लगातार देव वातावरण का निर्माण करता है। जिसके वजह से टीम के सदस्य प्रत्येक नए कार्य के लिए तुरंत नए देव वातावरण के साथ कोडिंग शुरू कर सकते हैं - चाहे आप कोई नई सुविधा बना रहे हों, बग को ठीक करना चाहते हों, या कोड समीक्षा पर काम करना चाहते हों। </sup>
            </div>
        </a>
    </p>
    <hr />
</div>

## यह क्या है?
यह एक बड़ी कंपनी के लिए सॉफ्टवेयर इंजीनियर को वेब डेवलपर (स्वयं सिखाया, कोई सीएस डिग्री नहीं) से जाने के लिए मेरी बहु-महीने की अध्ययन योजना है

![Coding at the whiteboard - from HBO's Silicon Valley](https://d3j2pkmjtin6ou.cloudfront.net/coding-at-the-whiteboard-silicon-valley.png)

यह नए सॉफ़्टवेयर इंजीनियरों या सॉफ़्टवेयर / वेब विकास से सॉफ़्टवेयर इंजीनियरिंग (जहां कंप्यूटर साइंस ज्ञान आवश्यक है) से स्विच करने के लिए है। यदि आपके पास कई वर्षों का अनुभव है और कई वर्षों के सॉफ्टवेयर इंजीनियरिंग अनुभव का दावा कर रहे हैं, तो एक कठिन साक्षात्कार की अपेक्षा करें।

यदि आपके पास सॉफ्टवेयर / वेब विकास के कई सालों का अनुभव है, तो ध्यान दें कि Google, अमेज़ॅन, फेसबुक और माइक्रोसॉफ्ट जैसी बड़ी सॉफ्टवेयर कंपनियों की दृष्टि में सॉफ्टवेयर इंजीनियरिंग सॉफ्टवेयर/वेब डेवलपमेंट से भिन्न है , और उन्हें कंप्यूटर साइंस ज्ञान की आवश्यकता होती है।

यदि आप एक विश्वसनीय इंजीनियर या सिस्टम इंजीनियर बनना चाहते हैं, तो वैकल्पिक सूची (नेटवर्किंग, सुरक्षा) से अधिक जानें।

---

## अनुक्रमणिका
- [यह क्या है?](#यह-क्या-है )
- [इसका उपयोग क्यों करे?](#इसका-उपयोग-क्यू-करे)
- [इसका कैसे उपयोग करे?](#इसका-कैसे-उपयोग-करे)
- [गूगल की मुद्रा में आ जाएँ](#गूगल-की-मुद्रा-में-आ-जाएँ)
- [क्या मुझे नौकरी मिली?](#क्या-मुझे-नौकरी-मिली)
- [मेरे साथ चले](#मेरे-साथ-चले)
- [अपने आप को कमजोर मत समझो ](#अपने-आप-को-कमजोर-मत-समझो )
- [गूगल के बारे में](#गूगल-के-बारे-में)
- [विडियो संसाधनों के बारे में](#विडियो-संसाधनों-के-बारे-में)
- [इंटरव्यू प्रकिया और साधारण इंटरव्यू तयारी](#interview-process--general-interview-prep)
- [इंटरव्यू के लिए एक भाषा चुने](#pick-one-language-for-the-interview)
- [प्रारंभ करने से पहले](#before-you-get-started)
- [इसमे क्या समाविष्ट नहीं हे](#इसमे-क्या-समाविष्ट-नहीं-हे)
- [पूर्व प्रयोजनीय ज्ञान](#prerequisite-knowledge)
- [दैनिक योजना](#the-daily-plan)
- [अल्गोरिथम जटिलता / बिग-O / Asymptotic analysis](#algorithmic-complexity--big-o--asymptotic-analysis)
- [डेटा संरचनाएं](#data-structures)
    - [ऐरे](#arrays)
    - [लिंक्ड लिस्ट](#linked-lists)
    - [स्टैक](#stack)
    - [क़ु](#queue)
    - [हैश टेबल](#hash-table)
- [अधिक जानकारी](#more-knowledge)
    - [बाइनरी सर्च](#binary-search)
    - [बिट-वाईस ऑपेरशन](#bitwise-operations)
- [ट्रीज](#trees)
    - [ट्रीज पृष्टभूमि और टिप्पणियाँ](#trees---notes--background)
    - [बाइनरी सर्च ट्री: BST](#binary-search-trees-bsts)
    - [हीप / प्रायोरिटी क्यू / बाइनरी हीप](#heap--priority-queue--binary-heap)
    - [ट्राइस](#tries)
    - [बैलेंस्ड सर्च ट्री](#balanced-search-trees)
    - [N-ary (K-ary, M-ary) ट्री](#n-ary-k-ary-m-ary-trees)
- [सॉर्टिंग](#sorting)
- [ग्राफ](#graphs)
- [और अधिक जानकारी](#even-more-knowledge)
    - [रिकर्शन](#recursion)
    - [डायनामिक प्रोग्रामिंग](#dynamic-programming)
    - [साहचर्य (Combinatorics) (n choose k) & संभावना](#combinatorics-n-choose-k--probability)
    - [NP, NP-Complete और सन्निकटन एल्गोरिदम](#np-np-complete-and-approximation-algorithms)
    - [गार्बेज कलेक्शन](#garbage-collection)
    - [कैश(Caches)](#caches)
    - [प्रोसेस और थ्रेड](#processes-and-threads)
    - [सिस्टम डिज़ाइन, स्केलेबिलिटी, डेटा हैंडलिंग](#system-design-scalability-data-handling)
    - [पेपर्स](#papers)
    - [यूनिकोड](#unicode)
    - [Emacs और vim](#emacs-and-vim)
    - [Unix कमांड लाइन उपकरण](#unix-command-line-tools)
    - [परिक्षण](#testing)
    - [डिजाइन पैटर्न्स](#design-patterns)
    - [निर्धारण](#scheduling)
    - [सिस्टम रूटीन लागू करें](#implement-system-routines)
    - [स्ट्रिंग खोज और तिकड़म](#string-searching--manipulations)
- [आखिरी समीक्षा](#final-review)
- [पुस्तकें](#books)
- [कोडिंग अभ्यास/चुनौतियाँ](#coding-exerciseschallenges)
- [एक बार जब आप इंटरव्यू के करीब हो](#once-youre-closer-to-the-interview)
- [आपका रिज्यूमे](#आपका-रिज्यूमे)
- [इंटरव्यू की सोंच](#be-thinking-of-for-when-the-interview-comes)
- [इंटरव्यूअर के लिए प्रश्न रखे](#have-questions-for-the-interviewer)
- [अतिरिक्त पढाई (जरुरत नहीं)](#additional-learnings-not-required)
    - [इनफार्मेशन थ्योरी](#information-theory)
    - [पारिटी और हैमिंग कोड](#parity--hamming-code)
    - [एन्थ्रोपी](#entropy)
    - [क्रिप्टोग्राफी](#cryptography)
    - [संक्षिप्तीकरण](#compression)
    - [नेटवर्किंग](#networking)
    - [संगणक सुरक्षा](#computer-security)
    - [पैरेलल प्रोग्रामिंग](#parallel-programming)
    - [Messaging, Serialization, and Queueing Systems](#messaging-serialization-and-queueing-systems)
    - [Fast Fourier Transform](#fast-fourier-transform)
    - [ब्लूम फ़िल्टर](#bloom-filter)
    - [van Emde Boas Trees](#van-emde-boas-trees)
    - [Augmented Data Structures](#augmented-data-structures)
    - [स्किप लिस्ट](#skip-lists)
    - [Network Flows](#network-flows)
    - [Disjoint Sets & Union Find](#disjoint-sets--union-find)
    - [फास्ट प्रोसेसिंग के लिए गणित](#math-for-fast-processing)
    - [Treap](#treap)
    - [लीनियर प्रोग्रामिंग](#linear-programming)
    - [ज्यामिति, कॉन्वेक्स हल](#geometry-convex-hull)
    - [डिस्क्रीट मैथ](#discrete-math)
    - [मशीन लर्निंग](#machine-learning)
    - [गो](#go)
- [कुछ विषयो की अधिक जानकारी](#additional-detail-on-some-subjects)
- [विडियो शृखला](#video-series)
- [जब आपको नौकरी मिल जाये](#computer-science-courses)

---

## इसका उपयोग क्यों करे?

मैंने जब ये परियोजना शुरू की, तब मैं स्टैक और  हीप में फर्क नहीं जानता था, मुझे नहीं पता था की Big-O क्या हे, ट्रीज क्या हे, या ग्राफ को पार कैसे करते हैं. अगर मुझे छाटने का अल्गोरिथम लिखना पड़ता तो मैं आपको ये बता सकता हु कि वो इतना ख़ास नहीं होगा. जो भी डाटा स्ट्रक्चर का मैंने उपयोग किया वो भाषा में समाविष्ट था, और वो कैसे काम करता हे उसकी कोई जानकारी मुझे नहीं थी. मैं कभी मेमोरी का संचालन नहीं करता, जब तक मेरी चलाई कोई प्रोसेस "out of
memory" का एरर न दे, और तब मुझे कोई वैकल्पिक हल ढूँढनाा पड़ता था. मैंने मेरी जिन्दगी में बहुत कम मल्टी-डायमेंशनल ऐरे और बहोत सारे associative ऐरे का उपयोग किया हे, पर मैंने कोई भी डाटा स्ट्रक्चर शुरू से नहीं लिखा था.
पर इस अध्ययन योजना का उपयोग करने बाद मेरा नौकरी लगने का आत्मविश्वास बहुत बढ़ा हें. यह एक लम्बी योजना हें. यह मेरे लिए बहुत महीनो तक चली. अगर आपको इनमें से कुछ पता हैं तो आपको कम वक्त लगेगा.


## इसका कैसे उपयोग करे?

नीचे सब कुछ एक रूपरेखा है, और आप ऊपर से नीचे के क्रम में पढ़े.

मैं  गिटहब के विशेष  मार्कडाउन का उपयोग कर रहा हूँ, प्रगति की जाँच करने के लिए कार्य सूचियों का प्रयोग करे.

- [x] एक नई शाखा बनाएँ ताकि आप इस तरह की वस्तुओं की जांच कर सकते हैं, बस कोष्ठक में एक एक्स डाले: [x]

[Github-flavored markdown की अधिक जानकारी](https://guides.github.com/features/mastering-markdown/#GitHub-flavored-markdown)

## कभी भी आप चालाक नहीं हो ऐसा ना सोचो

- सफल सॉफ्टवेयर इंजीनियर चालाक होते हें, पर बहुत लोगो को असुरक्षा होती है किी वो चालाक नहीं हैं ! 
- [The myth of the Genius Programmer](https://www.youtube.com/watch?v=0SARbwvhupQ)

## विडियो संसाधनों के बारे में

कुछ विडियो सिर्फ Coursera, EdX, or Lynda.com के वर्ग में दाखिला लेने का बाद ही उपलब्ध हैं. उन्हें MOOC कहा जाता हैं.
कभी-कभी कक्षाएं सत्र में नहीं होती हैं इसलिए आपको कुछ महीने इंतजार करना पड़ता है, इसलिए आपके पास पहुंच नहीं है। Lynda.com पाठ्यक्रम मुफ्त नहीं हैं

    I'd appreciate your help converting the MOOC video links to public sources to replace the online course विडियो over time. I like using university lectures.


## इंटरव्यू प्रकिया और साधारण इंटरव्यू तैयारी

[ ] [ABC: Always Be Coding](https://medium.com/always-be-coding/abc-always-be-coding-d5f8051afce2#.4heg8zvm4)
[ ] [Whiteboarding](https://medium.com/@dpup/whiteboarding-4df873dbba2e#.hf6jn45g1)
[ ] [Effective Whiteboarding during Programming Interviews](http://www.coderust.com/blog/2014/04/10/effective-whiteboarding-during-programming-interviews/)
[ ] Cracking The Coding Interview Set 1:
    - [ ] [Gayle L McDowell - Cracking The Coding Interview (विडियो)](https://www.youtube.com/watch?v=rEJzOhC5ZtQ)
    - [ ] [Cracking the Coding Interview with Author Gayle Laakmann McDowell (विडियो)](https://www.youtube.com/watch?v=aClxtDcdpsQ)
- [ ] बड़े ४ मैं नौकरी कैसे ले:
    - [ ] ['बड़े ४ मैं नौकरी कैसे ले - Amazon, Facebook, Google और Microsoft' (विडियो)](https://www.youtube.com/watch?v=YJZCUhxNCv8)

## इंटरव्यू के लिए एक संगणक भाषा चुने

इंटरव्यू में आप कोई भी एक भाषा जिसमे आप आरामदायक हो वो चुन सकते हैं, पर गूगल के लिए निम्नलिखित भाषाएँ अच्छी रहेगी:

- C++
- Java
- Python

आप निम्नलिखित भाषाएँ भी चुन सकते हैं, पर उन्हें सावधानी से चुने

- JavaScript
- Ruby

आपको भाषा में बहुत सहज होना चाहिए और जानकारी होनी चाहिए।

विकल्पों के बारे में अधिक पढ़ें:

- http://www.byte-by-byte.com/choose-the-right-language-for-your-coding-interview/
- http://blog.codingforinterviews.com/best-programming-language-jobs/

[भाषा संसाधनोंको यहाँ देखें](programming-language-resources.md)

क्योकि में मैं पढ़ रहा हूँ, आपको कुछ C, C++, और Python शामिल दिखेगा. वहाँ कुछ शामिल किताबें, नीचे आखिर में देख ले.

## पुस्तक सूची
यह मैंने जो इस्तेमाल किया था उससे छोटी सूची है यह आपको समय बचाने के लिए संक्षिप्त है

### इंटरव्यू प्रेप
- [ ]  प्रोग्रामिंग साक्षात्कार का खुलासा: आपकी अगली नौकरी, दूसरी संस्करण को लैंडिंग करने के लिए रहस्य
    - C++ और java में जवाब
    - यह कोडिंग साक्षात्कार के लिए क्रैकिंग के लिए एक अच्छा वार्म-अप है
    - बहुत मुश्किल नहीं है, सबसे अधिक समस्याएं आपको साक्षात्कार में जो दिखाई दे रही हैं उससे अधिक आसान हो सकती हैं (मैंने जो पढ़ा है)
- [ ] कोडिंग साक्षात्कार, 6 वें संस्करण
    - जावा में जवाब

यदि आपके पास बहुत अधिक समय है:

- [ ] [प्रोग्रामिंग साक्षात्कार के तत्व (सी ++ संस्करण)](https://www.amazon.com/Elements-Programming-Interviews-Insiders-Guide/dp/1479274836)
- [ ] प्रोग्रामिंग साक्षात्कार के तत्व (जावा संस्करण)
    - [किताब](https://www.amazon.com/Elements-Programming-Interviews-Java-Insiders/dp/1517435803/)
    - [कम्पेनियन प्रोजेक्ट - पुस्तक में हर समस्या के लिए विधि स्टब और टेस्ट](https://github.com/gardncl/elements-of-programming-interviews)

### कंप्यूटर आर्किटेक्चर

यदि कम समय पर:

- [ ] [ग्रेट कोड लिखें: वॉल्यूम 1: मशीन को समझना](https://www.amazon.com/Write-Great-Code-Understanding-Machine/dp/1593270038)
    - यह पुस्तक 2004 में प्रकाशित हुई थी, और कुछ समय पुरानी है, लेकिन संक्षिप्त में एक कम्प्यूटर को समझने के लिए यह एक बढ़िया संसाधन है।
    - लेखक ने एचएलए का आविष्कार किया, इसलिए नमक के एक अनाज के साथ एचएलए में उल्लेख और उदाहरण ले लीजिए। व्यापक रूप से उपयोग नहीं किया जाता है, लेकिन सभ्य उदाहरण कौन सी की तरह लग रहा है।
    - ये अध्याय आपको एक अच्छी नींव देने के लिए पढ़ने योग्य हैं:
        - अध्याय 2 - संख्यात्मक प्रतिनिधित्व
        - अध्याय 3 - बाइनरी अंकगणित और बिट ऑपरेशंस
        - अध्याय 4 - फ़्लोटिंग-प्वाइंट प्रस्तुति
        - अध्याय 5 - चरित्र प्रतिनिधित्व
        - अध्याय 6 - मेमोरी संगठन और एक्सेस
        - अध्याय 7 - संमिश्र डेटा प्रकार और स्मृति वस्तुएं
        - अध्याय 9 - सीपीयू वास्तुकला
        - अध्याय 10 - निर्देश सेट आर्किटेक्चर
        - अध्याय 11 - स्मृति वास्तुकला और संगठन
        
यदि आपके पास अधिक समय है (मुझे यह किताब चाहिए):

- [ ] [कंप्यूटर वास्तुकला, पांचवें संस्करण: एक मात्रात्मक दृष्टिकोण](https://www.amazon.com/dp/012383872X/)
    - एक अमीर, अधिक अप-टू-डेट (2011) के लिए, लेकिन लंबे समय तक उपचार

### भाषा विशिष्ट

**साक्षात्कार के लिए आपको भाषा चुननी होगी (ऊपर देखें)।** यहां मेरी सिफारिशें भाषा के अनुसार हैं मेरे पास सभी भाषाओं के लिए संसाधन नहीं हैं मैं अतिरिक्त स्वागत करता हूँ

यदि आप इनमें से किसी एक को पढ़ते हैं, तो आपको सभी डेटा संरचनाएं और एल्गोरिदम ज्ञान होना चाहिए, आपको कोडिंग समस्याएं शुरू करने की आवश्यकता होगी। **आप इस प्रोजेक्ट में सभी वीडियो व्याख्यान छोड़ सकते हैं** , अगर आप समीक्षा पसंद नहीं करते।

[यहां अतिरिक्त भाषा-विशिष्ट संसाधन हैं]((programming-language-resources.md)


### सी ++

मैंने इन दोनों को नहीं पढ़ा है, लेकिन वे बेहद रेटेड हैं और सेंडविक द्वारा लिखित हैं वह बहुत अच्छा है।

- [ ] [सी ++ में अल्गोरिदम, भाग 1-4: बुनियादी बातों, डेटा संरचना, छंटनी, खोज](https://www.amazon.com/Algorithms-Parts-1-4-Fundamentals-Structure/dp/0201350882/)
- [ ] [सी ++ भाग 5 में एल्गोरिदम: ग्राफ़ एल्गोरिदम](https://www.amazon.com/Algorithms-Part-Graph-3rd-Pt-5/dp/0201361183/)

यदि आपके पास सी ++ के लिए बेहतर सिफारिश है, तो कृपया मुझे बताएं एक व्यापक संसाधन की तलाश में

### जावा

- [ ] [एल्गोरिदम (सेडगेविक और वेन)](https://www.amazon.com/Algorithms-4th-Robert-Sedgewick/dp/032157351X/)
    - पुस्तक सामग्री के साथ वीडियो (और सेडगेविक!):
        - [एल्गोरिदम I](https://www.youtube.com/user/algorithmscourses/playlists?view=50&sort=dd&shelf_id=2)
        - [एल्गोरिदम II](https://www.youtube.com/user/algorithmscourses/playlists?shelf_id=3&view=50&sort=dd)
या:

- [ ] [जावा में डाटा स्ट्रक्चर और एल्गोरिदम](https://www.amazon.com/Data-Structures-Algorithms-Michael-Goodrich/dp/1118771338/)
    - गुडरिक, तामासिया, गोल्डवासेर द्वारा
    - यूसी बर्कले में सीएस परिचय पाठ्यक्रम के लिए वैकल्पिक पाठ के रूप में प्रयोग किया जाता है
    - नीचे दिए गए अजगर संस्करण पर मेरी पुस्तक रिपोर्ट देखें। यह पुस्तक उसी विषयों को शामिल करती है

### Python

- [ ] [पायथन में डेटा स्ट्रक्चर और एल्गोरिदम](https://www.amazon.com/Structures-Algorithms-Python-Michael-Goodrich/dp/1118290275/)
    - गुडरिक, तामासिया, गोल्डवासेर द्वारा
    - मुझे यह पुस्तक पसंद है यह सब कुछ और अधिक कवर किया
    - पायथनिक कोड
    - मेरी चमकती पुस्तक रिपोर्ट: https://startupnextdoor.com/book-report-data-structures-and-lgorithms-in-python/sss
    
### वैकल्पिक पुस्तकें

**कुछ लोग ये सुझाते हैं, लेकिन मुझे लगता है कि यह ज़्यादा पानी में जा रहा है, जब तक कि आपके पास कई सालों तक सॉफ्टवेयर इंजीनियरिंग अनुभव न हो और बहुत कठिन साक्षात्कार की अपेक्षा करें:**

- [ ] [एल्गोरिदम डिजाइन मैनुअल (स्कीएना)](http://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1849967202)
    - एक समीक्षा और समस्या पहचान के रूप में
    - एल्गोरिथ्म सूची हिस्सेदारी आप एक साक्षात्कार में मिल जाएगा कठिनाई के दायरे से परे है।
    - इस पुस्तक में 2 भाग हैं: 
        - डेटा संरचनाओं और एल्गोरिदम पर कक्षा पाठ्यपुस्तक
            - पेशेवरों:
                - एक अच्छी समीक्षा है क्योंकि किसी भी एल्गोरिदम पाठ्यपुस्तक होंगे
                - उद्योग और शिक्षा के क्षेत्र में समस्याओं को सुलझाने के अपने अनुभवों से अच्छी कहानियां
                - सी में कोड उदाहरण
            - विपक्ष:
                - CLRS के रूप में घने या अभेद्य हो सकता है, और कुछ मामलों में, CLRS कुछ विषयों के लिए एक बेहतर विकल्प हो सकता है
                - अध्याय 7, 8, 9 का पालन करने की कोशिश करने के लिए दर्दनाक हो सकता है, क्योंकि कुछ वस्तुएं अच्छी तरह समझाई नहीं जाती हैं या मुझे जितना अधिक मस्तिष्क की ज़रूरत नहीं है
                - मुझे गलत मत बताना: मुझे स्कीएना, उनकी शिक्षण शैली और व्यवहार, लेकिन मैं स्टोनी ब्रूक सामग्री नहीं हो सकता
        - एल्गोरिथ्म सूची:
            - यह वास्तविक कारण है कि आप इस पुस्तक को खरीदते हैं।
            - इस भाग के बारे में जानने के लिए एक बार मैं इसके माध्यम से अपना रास्ता बना लिया है यहाँ अद्यतन होगा।
    - Kindle पर इसे किराए पर कर सकते हैं
    - अच्छे दामों पर पाठ्य पुस्तकें के लिए Half.com एक महान संसाधन है
    - उत्तर:
        - [समाधान की](http://www.algorithm.cs.sunysb.edu/algowiki/index.php/The_Algorithms_Design_Manual_(Second_Edition))
        - [समाधान की](http://blog.panictank.net/category/algorithmndesignmanualsolutions/page/2/)
    - [शुद्धिपत्र](http://www3.cs.stonybrook.edu/~skiena/algorist/book/errata)
    
- [ ] [एल्गोरिदम का परिचय]((https://www.amazon.com/Introduction-Algorithms-3rd-MIT-Press/dp/0262033844))
    - **महत्वपूर्ण:** इस पुस्तक को पढ़ना केवल सीमित मूल्य होगा। यह पुस्तक एल्गोरिदम और डेटा संरचनाओं की एक अच्छी समीक्षा है, लेकिन आपको यह नहीं सिखाती कि अच्छे कोड कैसे लिखें। आपको एक सभ्य समाधान को कुशलतापूर्वक कोडित करने में सक्षम होना होगा।
    - अच्छे दामों पर पाठ्य पुस्तकें के लिए Half.com एक महान संसाधन है
    - उर्फ सीएलआर, कभी कभी सीएलआरएस, क्योंकि स्टीन को खेल में देर हो गई थी
 - [ ] [Programming Pearls](http://www.amazon.com/Programming-Pearls-2nd-Jon-Bentley/dp/0201657880)
    - पहले अध्यायों में प्रोग्रामिंग समस्याओं (कुछ बहुत पुराने डेटा टेप का उपयोग करते हुए) के लिए चतुर समाधान प्रस्तुत करते हैं, लेकिन यह सिर्फ एक परिचय है। यह प्रोग्राम डिजाइन और आर्किटेक्चर पर एक गाइडबुक है, जो कोड कोड जैसा है, लेकिन बहुत छोटा है।

- ~~शेन द्वारा "एल्गोरिदम और प्रोग्रामिंग: प्रॉब्लम एंड सॉल्यूशंस"~~
    - एक अच्छी किताब, लेकिन कई पन्नों पर समस्याओं के माध्यम से काम करने के बाद मैं पास्कल से निराश हो गया, जबकि लूप, 1-अनुक्रमित सरणियां, और अस्पष्ट पद की स्थिति की संतुष्टि परिणाम 
    - बल्कि किसी अन्य पुस्तक या ऑनलाइन कोडिंग समस्याओं से कोडिंग समस्याओं पर समय बिताना होगा।

## प्रारंभ करने से पहले

इस सूची में कई महीनों से वृद्धि हुई है, और हाँ, यह एक तरह से हाथ से बाहर हो गयी हैं

नीचे कुछ गलतिया हैं जो मैंने की हैं तो आपका अनुभव बेहतर होगा

### १. आपसे यह सब याद नहीं होगा

मैंने घंटो वीडियो के विडियो देखे और टिप्पणिया लिखी, और महीनो बाद मुझे कुछ याद नहीं रहा. सबकी समीक्षा करने के लिए मैंने 3 दिन मेरी टिप्पणीयो और flashcards बनाने में बितायें 
कृपया पढ़ें तो आप मेरी गलतियां नहीं करेंगे:

[कंप्यूटर विज्ञान ज्ञान को बनाए रखना](https://startupnextdoor.com/retaining-computer-science-knowledge/)

### २. फ़्लैशकार्ड्स का उपयोग कीजिये 

इस समस्या को हल करने के लिए, मैंने एक छोटे से फ्लैशकार्ड साइट बनाई जहां मैं 2 प्रकार के फ्लैशकार्ड जोड़ सकता था: सामान्य और कोड प्रत्येक कार्ड के पास भिन्न स्वरूपण है।

मैंने एक मोबाइल-पहले वेबसाइट बनाई है, इसलिए मैं अपने फोन और टैबलेट पर समीक्षा कर सकता हूं, जहां कहीं भी हूं।

अपना खुद का मुफ्त बनाएं:
 - [फ़्लैशकार्ड साइट रेपो] (https://github.com/jwasham/computer-science-flash-cards)
 - [मेरे फ़्लैश कार्ड डेटाबेस (पुराने - 1200 कार्ड) :](https://github.com/jwasham/computer-science-flash-cards/blob/main/cards-jwasham.db)
 - [मेरा फ़्लैश कार्ड डेटाबेस (नया - 1800 कार्ड) :](https://github.com/jwasham/computer-science-flash-cards/blob/main/cards-jwasham-extreme.db)

ध्यान रखें मैं जहाज़ के ऊपर गया और विधानसभा भाषा और पायथन तुल्यता से लेकर मशीन सीखने और आंकड़ों तक सब कुछ कवर करने वाले कार्ड हैं। इसकी आवश्यकता के लिए यह बहुत अधिक है

**फ्लैशकार्ड्स पर ध्यान दें:** पहली बार जब आप पहचानते हैं कि आपको जवाब पता है, तो इसे ज्ञात के रूप में चिह्नित नहीं करें आपको उसी कार्ड को देखना होगा और उसे सच में पता होना चाहिए इससे पहले कि आप इसे सच में जानते हैं। पुनरावृत्ति आपके दिमाग में गहरा ज्ञान डाल देगा।

मेरी फ्लैशकार्ड साइट का उपयोग करने का एक विकल्प अनकी है , जिसे कई बार मेरी सिफारिश की गई है यह आपको याद रखने में मदद करने के लिए पुनरावृत्ति प्रणाली का उपयोग करता है यह उपयोगकर्ता के अनुकूल है, सभी प्लेटफ़ॉर्म पर उपलब्ध है और इसमें क्लाउड सिंक सिस्टम है यह आईओएस पर $ 25 का खर्च है, लेकिन अन्य प्लेटफार्मों पर मुफ्त है

अनू प्रारूप में मेरा फ्लैशकार्ड डाटाबेस: https://ankiweb.net/shared/info/25173560 (धन्यवाद @ एक्सआईवेनिया )



### 3. समीक्षा करें, समीक्षा करें, समीक्षा करें

मैं ASCII ओएसआई स्टैक, बिग-ओ नोटेशन और अधिक पर धोखा पत्रों का एक सेट रखता हूं। मेरे पास कुछ खाली समय है जब मैं उन्हें पढ़ता हूं।

एक आधे घंटे के लिए प्रोग्रामिंग समस्याओं से एक ब्रेक ले लो और अपने flashcards के माध्यम से जाना

### 4. फोकस

ऐसे कई विकर्षण हैं जो कि मूल्यवान समय ले सकते हैं फोकस और एकाग्रता कठिन हैं

## इसमे क्या समाविष्ट नहीं हे

यह बड़ी सूचि गूगल इंटरव्यू टिप्पणियों से व्यक्तिगत कार्य सूचि से बनायीं गयी थी. निचे कुछ प्रचलित टेक्नोलॉजी हैं पर उन्हें टिप्पणियो में समाविस्ट नहीं किया गया हैं.

- SQL
- Javascript
- HTML, CSS, and other front-end technologies

## दैनिक योजना

कुछ विषय एक दिन ले सकते हैं और कुछ ज्यादा. कुछो की सिर्फ पढाई हो सकती हैं पर अमल नहीं हो सकता.

हर दिन मैं निचली सूची से एक विषय लेता हूँ, उसका विडियो देखता हूँ, और उसका अमल नीचे दिए तरह करता हूँ:
- C - struct और function का उपयोग करके  जो  struct * या args का  उपयोग करते हैं.
- C++ - built-in types का उपयोग न करके
- C++ - built-in types का उपयोग करके, जैसे STL की std::list, linked list के लिए
- Python - built-in types का उपयोग करके (Python का अभ्यास रखने के लिए)
- और यह सुनिश्चित करने के लिए परीक्षण लिखते हैं कि मैं इसे सही कर रहा हूं, कभी-कभी बस सरल () कथन का उपयोग कर
- आप जावा या कुछ और कर सकते हैं, यह सिर्फ मेरी बात है
आपको इन सभी की ज़रूरत नहीं है साक्षात्कार के लिए आपको केवल एक ही भाषा की आवश्यकता है

इन सब में कोड क्यों?
- अभ्यास, अभ्यास, अभ्यास, जब तक मैं इससे बीमार न हो, और यह कोई समस्या नहीं कर सकता (कुछ बहुत बढ़िया मामलों और याद रखने के लिए बही-खाता विवरण)
- कच्ची बाधाओं के भीतर काम करना (कचरा संग्रहण की सहायता के बिना स्मृति को आवंटित करना / मुक्त करना (पायथन को छोड़कर))
- अंतर्निहित प्रकारों का उपयोग करें, इसलिए मुझे वास्तविक दुनिया के उपयोग के लिए निर्मित उपकरणों का उपयोग करने का अनुभव है (उत्पादन में अपनी स्वयं की लिंक्ड सूची कार्यान्वयन नहीं लिखना)

मेरे पास हर विषय के लिए ये सब करने का समय नहीं है, लेकिन मैं कोशिश करूँगा

आप यहां अपना कोड देख सकते हैं:
 - [C](https://github.com/jwasham/practice-c)
 - [C++](https://github.com/jwasham/practice-cpp)
 - [Python](https://github.com/jwasham/practice-python)
 
आपको हर एल्गोरिथम याद करने की आवश्यकता नहीं है।

एक व्हाइटबोर्ड या कागज़ पर कोड लिखें, कंप्यूटर नहीं। कुछ नमूना इनपुट के साथ टेस्ट करें फिर इसे कंप्यूटर पर जांचें

 ## पूर्वाभ्यास ज्ञान

 - [ ] **C जानें**
    - सी हर जगह है आप पुस्तकों, व्याख्यान, वीडियो, हर जगह जब आप पढ़ रहे हैं, में उदाहरण देखेंगे।
    - [ ] [सी प्रोग्रामिंग भाषा, खंड 2](https://www.amazon.com/Programming-Language-Brian-W-Kernighan/dp/0131103628)
        - यह एक छोटी पुस्तक है, लेकिन यह आपको सी भाषा पर एक महान संभाल देगा और यदि आप इसे थोड़ा अभ्यास करते हैं तो आपको जल्दी से कुशल मिलेगा। सी आपको यह समझने में मदद करता है कि प्रोग्राम और मेमोरी कैसे काम करते हैं 
        - [सवालों के जवाब](https://github.com/lekkas/c-algorithms)

- [ ] **कंप्यूटर एक प्रोग्राम की प्रक्रिया कैसे करते हैं:**
    - [ ] [कैसे सीपीयू प्रोग्राम निष्पादित करता है (वीडियो)](https://www.youtube.com/watch?v=42KTvGYQYnA)
    - [ ] [मशीन कोड निर्देश (वीडियो)](https://www.youtube.com/watch?v=Mv2XQgpbTNE)

## एल्गोरिथम जटिलता / बिग-ओ / असिम्प्टोोटिक विश्लेषण
- लागू करने के लिए कुछ भी नहीं
- [ ] [ हार्वर्ड सीएस 50 - असिमप्टोटीक नोटेशन (वीडियो)](https://www.youtube.com/watch?v=iOq5kSKqeR4)
- [ ] [ बिग ओ नोट्स (सामान्य त्वरित ट्यूटोरियल) (वीडियो)](https://www.youtube.com/watch?v=V6mKVRU1evU)
- [ ] [ बिग ओ नोटेशन (और ओमेगा और थीटा) - सर्वोत्तम गणितीय व्याख्या (वीडियो)](https://www.youtube.com/watch?v=ei-A_wy5Yxw&index=2&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN)
- [ ] Skiena:
    - [विडियो](https://www.youtube.com/watch?v=gSyDMtdPNpU&index=2&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
    - [स्लाइड](http://www3.cs.stonybrook.edu/~algorith/video-lectures/2007/lecture2.pdf)
- [ ] [एल्गोरिथ्म जटिलता विश्लेषण के लिए एक कोमल परिचय](http://discrete.gr/complexity/)
- [ ] [विकास के आदेश (वीडियो)](https://class.coursera.org/algorithmicthink1-004/lecture/59)
- [ ] [Asymptotics (विडियो)](https://class.coursera.org/algorithmicthink1-004/lecture/61)
- [ ] [UC बर्कले Big O (विडियो)](https://youtu.be/VIS4YDpuP98)
- [ ] [UC बर्कले Big Omega (विडियो)](https://youtu.be/ca3e7UVmeUc)
- [ ] [Amortized Analysis (विडियो)](https://www.youtube.com/watch?v=B3SpQZaAZP4&index=10&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN)
- [ ] [Illustrating "Big O" (विडियो)](https://class.coursera.org/algorithmicthink1-004/lecture/63)
- [ ] टॉपकोडर (पुनरावृत्ति संबंध और मास्टर प्रमेय भी शामिल है):
    - [कम्प्यूटेशनल जटिलता: धारा 1](https://www.topcoder.com/community/data-science/data-science-tutorials/computational-complexity-section-1/)
    - [कम्प्यूटेशनल जटिलता: धारा 2](https://www.topcoder.com/community/data-science/data-science-tutorials/computational-complexity-section-2/)
- [ ] [Cheat sheet](http://bigocheatsheet.com/)



##  डेटा संरचनाएं

- ### Arrays
    - एक स्वचालित रीसाइज़िंग वेक्टर को लागू करें
    - [ ] विवरण:
        - [एरे  (विडियो)](https://www.coursera.org/learn/data-structures/lecture/OsBSF/arrays)
        - [Dynamic Arrays (विडियो)](https://www.coursera.org/learn/data-structures/lecture/EwbnV/dynamic-arrays)
    - [ ] 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
            - 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
        - [ ] capacity() - number of items it can hold
        - [ ] is_empty()
        - [ ] at(index) - returns item at given index, blows up if index out of bounds
        - [ ] push(item)
        - [ ] insert(index, item) - inserts item at index, shifts that index's value and trailing elements to the right
        - [ ] prepend(item) - can use insert above at index 0
        - [ ] pop() - remove from end, return value
        - [ ] delete(index) - delete item at index, shifting all trailing elements left
        - [ ] remove(item) - looks for value and removes index holding it (even if in multiple places)
        - [ ] find(item) - looks for value and returns first index with that value, -1 if not found
        - [ ] resize(new_capacity) // private function
            - when you reach capacity, resize to double the size
            - when popping an item, if size is 1/4 of capacity, resize to half
    - [ ] Time
        - O(1) to add/remove at end (amortized for allocations for more space), index, or update
        - O(n) to insert/remove elsewhere
    - [ ] Space
        - contiguous in memory, so proximity helps performance
        - space needed = (array capacity, which is >= n) * size of item, but even if 2n, still O(n)

- ### Linked Lists
    - [ ] Description:
        - [ ] [Singly Linked Lists (विडियो)](https://www.coursera.org/learn/data-structures/lecture/kHhgK/singly-linked-lists)
        - [ ] [CS 61B - Linked Lists (विडियो)](https://www.youtube.com/watch?v=sJtJOtXCW_M&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd&index=5)
    - [ ] [C Code (विडियो)](https://www.youtube.com/watch?v=QN6FPiD0Gzo)
            - not the whole video, just portions about Node struct and memory allocation.
    - [ ] Linked List vs Arrays:
        - [Core Linked Lists Vs Arrays (विडियो)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/rjBs9/core-linked-lists-vs-arrays)
        - [In The Real World Linked Lists Vs Arrays (विडियो)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/QUaUd/in-the-real-world-lists-vs-arrays)
    - [ ] [why you should avoid linked lists (विडियो)](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):
        - [ ] 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)
        - [ ] push_front(value) - adds an item to the front of the list
        - [ ] pop_front() - remove front item and return its value
        - [ ] push_back(value) - adds an item at the end
        - [ ] pop_back() - removes end item and returns its value
        - [ ] front() - get value of front item
        - [ ] back() - get value of end item
        - [ ] insert(index, value) - insert value at index, so current item at that index is pointed to by new item at index
        - [ ] erase(index) - removes node at given index
        - [ ] value_n_from_end(n) - returns the value of the node at nth position from the end of the list
        - [ ] reverse() - reverses the list
        - [ ] remove_value(value) - removes the first item in the list with this value
    - [ ] Doubly-linked List
        - [Description (विडियो)](https://www.coursera.org/learn/data-structures/lecture/jpGKD/doubly-linked-lists)
        - No need to implement

- ### Stack
    - [ ] [Stacks (विडियो)](https://www.coursera.org/learn/data-structures/lecture/UdKzQ/stacks)
    - [ ] Will not implement. Implementing with array is trivial.

- ### Queue
    - [ ] [Queue (विडियो)](https://www.coursera.org/learn/data-structures/lecture/EShpq/queue)
    - [ ] [Circular buffer/FIFO](https://en.wikipedia.org/wiki/Circular_buffer)
    - [ ] Implement using linked-list, with tail pointer:
        - enqueue(value) - adds value at position at tail
        - dequeue() - returns value and removes least recently added element (front)
        - empty()
    - [ ] Implement using fixed-sized array:
        - enqueue(value) - adds item at end of available storage
        - dequeue() - returns value and removes least recently added element
        - empty()
        - full()
    - [ ] Cost:
        - a bad implementation using linked list where you enqueue at head and dequeue at tail would be O(n)
            because you'd need the next to last element, causing a full traversal each dequeue
        - enqueue: O(1) (amortized, linked list and array [probing])
        - dequeue: O(1) (linked list and array)
        - empty: O(1) (linked list and array)
    
- ### Hash table
    - [ ] विडियो:
        - [ ] [Hashing with Chaining (विडियो)](https://www.youtube.com/watch?v=0M_kIqhwbFo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=8)
        - [ ] [Table Doubling, Karp-Rabin (विडियो)](https://www.youtube.com/watch?v=BRO7mVIFt08&index=9&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
        - [ ] [Open Addressing, Cryptographic Hashing (विडियो)](https://www.youtube.com/watch?v=rvdJDijO2Ro&index=10&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
        - [ ] [PyCon 2010: The Mighty Dictionary (विडियो)](https://www.youtube.com/watch?v=C4Kc8xzcA68)
        - [ ] [(Advanced) Randomization: Universal & Perfect Hashing (विडियो)](https://www.youtube.com/watch?v=z0lJ2k0sl1g&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=11)
        - [ ] [(Advanced) Perfect hashing (विडियो)](https://www.youtube.com/watch?v=N0COwN14gt0&list=PL2B4EEwhKD-NbwZ4ezj7gyc_3yNrojKM9&index=4)
    
    - [ ] Online Courses:
        - [ ] [Core Hash Tables (विडियो)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/m7UuP/core-hash-tables)
        - [ ] [Data Structures (विडियो)](https://www.coursera.org/learn/data-structures/home/week/3)
        - [ ] [Phone Book Problem (विडियो)](https://www.coursera.org/learn/data-structures/lecture/NYZZP/phone-book-problem)
        - [ ] distributed hash tables:
            - [Instant Uploads And Storage Optimization In Dropbox (विडियो)](https://www.coursera.org/learn/data-structures/lecture/DvaIb/instant-uploads-and-storage-optimization-in-dropbox)
            - [Distributed Hash Tables (विडियो)](https://www.coursera.org/learn/data-structures/lecture/tvH8H/distributed-hash-tables)
    
    - [ ] 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

- ### Endianness
    - [ ] [Big And Little Endian](https://www.cs.umd.edu/class/sum2003/cmsc311/Notes/Data/endian.html)
    - [ ] [Big Endian Vs Little Endian (विडियो)](https://www.youtube.com/watch?v=JrNF0KRAlyo)
    - [ ] [Big And Little Endian Inside/Out (विडियो)](https://www.youtube.com/watch?v=oBSuXP-1Tc0)
        - Very technical talk for kernel devs. Don't worry if most is over your head.
        - The first half is enough.

- ### Binary search
    - [ ] [Binary Search (विडियो)](https://www.youtube.com/watch?v=D5SrAga1pno)
    - [ ] [Binary Search (विडियो)](https://www.khanacademy.org/computing/computer-science/algorithms/binary-search/a/binary-search)
    - [ ] [detail](https://www.topcoder.com/community/data-science/data-science-tutorials/binary-search/)
    - [ ] 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/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:
            [Bit Manipulation (विडियो)](https://www.youtube.com/watch?v=7jkIUgLC29I)
        - [ ] [C Programming Tutorial 2-10: Bitwise Operators (विडियो)](https://www.youtube.com/watch?v=d0AwjSpNXR0)
        - [ ] [Bit Manipulation](https://en.wikipedia.org/wiki/Bit_manipulation)
        - [ ] [Bitwise Operation](https://en.wikipedia.org/wiki/Bitwise_operation)
        - [ ] [Bithacks](https://graphics.stanford.edu/~seander/bithacks.html)
        - [ ] [The Bit Twiddler](http://bits.stephan-brumme.com/)
        - [ ] [The Bit Twiddler Interactive](http://bits.stephan-brumme.com/interactive.html)
    - [ ] 2s and 1s complement
        - [Binary: Plusses & Minuses (Why We Use Two's Complement) (विडियो)](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
        - [4 ways to count bits in a byte (विडियो)](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)
    - [ ] round to next power of 2:
        - [Round Up To Next Power Of Two](http://bits.stephan-brumme.com/roundUpToNextPowerOfTwo.html)
    - [ ] swap values:
        - [Swap](http://bits.stephan-brumme.com/swap.html)
    - [ ] absolute value:
        - [Absolute Integer](http://bits.stephan-brumme.com/absInteger.html)

## Trees

- ### Trees - Notes & Background
    - [ ] [Series: Trees (विडियो)](https://www.coursera.org/learn/data-structures/lecture/95qda/trees)
    - basic tree construction
    - traversal
    - manipulation algorithms
    - BFS (breadth-first search)
        - [MIT (विडियो)](https://www.youtube.com/watch?v=s-CYnVz-uh4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=13)
        - level order (BFS, using queue)
            time complexity: O(n)
            space complexity: best: O(1), worst: O(n/2)=O(n)
    - DFS (depth-first search)
        - [MIT (विडियो)](https://www.youtube.com/watch?v=AfSk24UTFS8&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=14)
        - notes:
            time complexity: O(n)
            space complexity:
                best: O(log n) - avg. height of tree
                worst: O(n)
        - inorder (DFS: left, self, right)
        - postorder (DFS: left, right, self)
        - preorder (DFS: self, left, right)

- ### Binary search trees: BSTs
    - [ ] [Binary Search Tree Review (विडियो)](https://www.youtube.com/watch?v=x6At0nzX92o&index=1&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
    - [ ] [Series (विडियो)](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
    - [ ] [Introduction (विडियो)](https://www.coursera.org/learn/data-structures/lecture/E7cXP/introduction)
    - [ ] [MIT (विडियो)](https://www.youtube.com/watch?v=9Jry5-82I68)
    - C/C++:
        - [ ] [Binary search tree - Implementation in C/C++ (विडियो)](https://www.youtube.com/watch?v=COZK7NATh4k&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=28)
        - [ ] [BST implementation - memory allocation in stack and heap (विडियो)](https://www.youtube.com/watch?v=hWokyBoo0aI&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=29)
        - [ ] [Find min and max element in a binary search tree (विडियो)](https://www.youtube.com/watch?v=Ut90klNN264&index=30&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
        - [ ] [Find height of a binary tree (विडियो)](https://www.youtube.com/watch?v=_pnqMz5nrRs&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=31)
        - [ ] [Binary tree traversal - breadth-first and depth-first strategies (विडियो)](https://www.youtube.com/watch?v=9RHO6jU--GU&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=32)
        - [ ] [Binary tree: Level Order Traversal (विडियो)](https://www.youtube.com/watch?v=86g8jAQug04&index=33&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
        - [ ] [Binary tree traversal: Preorder, Inorder, Postorder (विडियो)](https://www.youtube.com/watch?v=gm8DUJJhmY4&index=34&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
        - [ ] [Check if a binary tree is binary search tree or not (विडियो)](https://www.youtube.com/watch?v=yEwSGhSsT0U&index=35&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
        - [ ] [Delete a node from Binary Search Tree (विडियो)](https://www.youtube.com/watch?v=gcULXE7ViZw&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=36)
        - [ ] [Inorder Successor in a binary search tree (विडियो)](https://www.youtube.com/watch?v=5cPbNCrdotA&index=37&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
    - [ ] Implement:
        - [ ] insert    // insert value into tree
        - [ ] get_node_count // get count of values stored
        - [ ] print_values // prints the values in the tree, from min to max
        - [ ] delete_tree
        - [ ] is_in_tree // returns true if given value exists in the tree
        - [ ] get_height // returns the height in nodes (single node's height is 1)
        - [ ] get_min   // returns the minimum value stored in the tree
        - [ ] get_max   // returns the maximum value stored in the tree
        - [ ] is_binary_search_tree
        - [ ] delete_value
        - [ ] get_successor // returns next-highest value in tree after given value, -1 if none

- ### 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 (विडियो)](https://www.coursera.org/learn/data-structures/lecture/2OpTs/introduction)
    - [ ] [Naive Implementations (विडियो)](https://www.coursera.org/learn/data-structures/lecture/z3l9N/naive-implementations)
    - [ ] [Binary Trees (विडियो)](https://www.coursera.org/learn/data-structures/lecture/GRV2q/binary-trees)
    - [ ] [Tree Height Remark (विडियो)](https://www.coursera.org/learn/data-structures/supplement/S5xxz/tree-height-remark)
    - [ ] [Basic Operations (विडियो)](https://www.coursera.org/learn/data-structures/lecture/0g1dl/basic-operations)
    - [ ] [Complete Binary Trees (विडियो)](https://www.coursera.org/learn/data-structures/lecture/gl5Ni/complete-binary-trees)
    - [ ] [Pseudocode (विडियो)](https://www.coursera.org/learn/data-structures/lecture/HxQo9/pseudocode)
    - [ ] [Heap Sort - jumps to start (विडियो)](https://youtu.be/odNJmw5TOEE?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3291)
    - [ ] [Heap Sort (विडियो)](https://www.coursera.org/learn/data-structures/lecture/hSzMO/heap-sort)
    - [ ] [Building a heap (विडियो)](https://www.coursera.org/learn/data-structures/lecture/dwrOS/building-a-heap)
    - [ ] [MIT: Heaps and Heap Sort (विडियो)](https://www.youtube.com/watch?v=B7hVxCmfPtM&index=4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
    - [ ] [CS 61B Lecture 24: Priority Queues (विडियो)](https://www.youtube.com/watch?v=yIUFT6AKBGE&index=24&list=PL4BBB74C7D2A1049C)
    - [ ] [Linear Time BuildHeap (max-heap)](https://www.youtube.com/watch?v=MiyLo8adrWw)
    - [ ] Implement a max-heap:
        - [ ] insert
        - [ ] sift_up - needed for insert
        - [ ] get_max - returns the max item, without removing it
        - [ ] get_size() - return number of elements stored
        - [ ] 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
        - [ ] 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).

- ### 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.
    - [ ] [Notes on Data Structures and Programming Techniques](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Tries)
    - [ ] Short course विडियो:
        - [ ] [Introduction To Tries (विडियो)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/08Xyf/core-introduction-to-tries)
        - [ ] [Performance Of Tries (विडियो)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/PvlZW/core-performance-of-tries)
        - [ ] [Implementing A Trie (विडियो)](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/data-science/data-science-tutorials/using-tries/)
    - [ ] [Stanford Lecture (real world use case) (विडियो)](https://www.youtube.com/watch?v=TJ8SkcUSdbU)
    - [ ] [MIT, Advanced Data Structures, Strings (can get pretty obscure about halfway through)](https://www.youtube.com/watch?v=NinWEPPrkDQ&index=16&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf)

- ### Balanced search trees
    - Know least one type of balanced binary tree (and know how it's implemented):
    - "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
        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.
    - [ ] [Self-balancing binary search tree](https://en.wikipedia.org/wiki/Self-balancing_binary_search_tree)

    - [ ] **AVL trees**
        - In practice:
            From what I can tell, these aren't used much in practice, but I could see where they would be:
            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).
        - [ ] [MIT AVL Trees / AVL Sort (विडियो)](https://www.youtube.com/watch?v=FNeL18KsWPc&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=6)
        - [ ] [AVL Trees (विडियो)](https://www.coursera.org/learn/data-structures/lecture/Qq5E0/avl-trees)
        - [ ] [AVL Tree Implementation (विडियो)](https://www.coursera.org/learn/data-structures/lecture/PKEBC/avl-tree-implementation)
        - [ ] [Split And Merge](https://www.coursera.org/learn/data-structures/lecture/22BgE/split-and-merge)

    - [ ] **Splay trees**
        - 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.
        - [ ] [CS 61B: Splay Trees (विडियो)](https://www.youtube.com/watch?v=Najzh1rYQTo&index=23&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd)
        - [ ] MIT Lecture: Splay Trees:
            - Gets very mathy, but watch the last 10 minutes for sure.
            - [Video](https://www.youtube.com/watch?v=QnPl_Y6EqMo)

    - [ ] **2-3 search trees**
        - In practice:
            2-3 trees have faster inserts at the expense of slower searches (since height is more compared to AVL trees).
        - You would use 2-3 tree very rarely because its implementation involves different types of nodes. Instead, people use Red Black trees.
        - [ ] [23-Tree Intuition and Definition (विडियो)](https://www.youtube.com/watch?v=C3SsdUqasD4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=2)
        - [ ] [Binary View of 23-Tree](https://www.youtube.com/watch?v=iYvBtGKsqSg&index=3&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
        - [ ] [2-3 Trees (student recitation) (विडियो)](https://www.youtube.com/watch?v=TOb1tuEZ2X4&index=5&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)

    - [ ] **2-3-4 Trees (aka 2-4 trees)**
        - In practice:
            For every 2-4 tree, there are corresponding red–black trees with data elements in the same order. The insertion and deletion
            operations on 2-4 trees are also equivalent to color-flipping and rotations in red–black trees. This makes 2-4 trees an
            important tool for understanding the logic behind red–black trees, and this is why many introductory algorithm texts introduce
            2-4 trees just before red–black trees, even though **2-4 trees are not often used in practice**.
        - [ ] [CS 61B Lecture 26: Balanced Search Trees (विडियो)](https://www.youtube.com/watch?v=zqrqYXkth6Q&index=26&list=PL4BBB74C7D2A1049C)
        - [ ] [Bottom Up 234-Trees (विडियो)](https://www.youtube.com/watch?v=DQdMYevEyE4&index=4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
        - [ ] [Top Down 234-Trees (विडियो)](https://www.youtube.com/watch?v=2679VQ26Fp4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=5)

    - [ ] **B-Trees**
        - 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.
        - [ ] [B-Tree](https://en.wikipedia.org/wiki/B-tree)
        - [ ] [Introduction to B-Trees (विडियो)](https://www.youtube.com/watch?v=I22wEC1tTGo&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=6)
        - [ ] [B-Tree Definition and Insertion (विडियो)](https://www.youtube.com/watch?v=s3bCdZGrgpA&index=7&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
        - [ ] [B-Tree Deletion (विडियो)](https://www.youtube.com/watch?v=svfnVhJOfMc&index=8&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
        - [ ] [MIT 6.851 - Memory Hierarchy Models (विडियो)](https://www.youtube.com/watch?v=V3omVLzI0WE&index=7&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf)
                - covers cache-oblivious B-Trees, very interesting data structures
                - the first 37 minutes are very technical, may be skipped (B is block size, cache line size)

    - [ ] **Red/black trees**
        - 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,
            but it makes them valuable building blocks in other data structures which provide worst-case guarantees;
            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.
        - [ ] [Aduni - Algorithms - Lecture 4 
            (link jumps to starting point) (विडियो)](https://youtu.be/1W3x0f_RmUo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3871)
        - [ ] [Aduni - Algorithms - Lecture 5 (विडियो)](https://www.youtube.com/watch?v=hm2GHwyKF1o&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=5)
        - [ ] [Black Tree](https://en.wikipedia.org/wiki/Red%E2%80%93black_tree)
        - [ ] [An Introduction To Binary Search And Red Black Tree](https://www.topcoder.com/community/data-science/data-science-tutorials/an-introduction-to-binary-search-and-red-black-trees/)

- ### N-ary (K-ary, M-ary) trees
    - note: the N or K is the branching factor (max branches)
        - binary trees are a 2-ary tree, with branching factor = 2
        - 2-3 trees are 3-ary
    - [ ] [K-Ary Tree](https://en.wikipedia.org/wiki/K-ary_tree)

## 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?")
        - [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/)
        - [Sorting Algorithms - Stability](http://homepages.math.uic.edu/~leon/cs-mcs401-s08/handouts/stability.pdf)
    - [ ] Which algorithms can be used on linked lists? Which on arrays? Which on both?
        - 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.

- [ ] [Bubble Sort (विडियो)](https://www.youtube.com/watch?v=P00xJgWzz2c&index=1&list=PL89B61F78B552C1AB)
- [ ] [Analyzing Bubble Sort (विडियो)](https://www.youtube.com/watch?v=ni_zk257Nqo&index=7&list=PL89B61F78B552C1AB)
- [ ] [Insertion Sort, Merge Sort (विडियो)](https://www.youtube.com/watch?v=Kg4bqzAqRBM&index=3&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
- [ ] [Insertion Sort (विडियो)](https://www.youtube.com/watch?v=c4BRHC7kTaQ&index=2&list=PL89B61F78B552C1AB)
- [ ] [Merge Sort (विडियो)](https://www.youtube.com/watch?v=GCae1WNvnZM&index=3&list=PL89B61F78B552C1AB)
- [ ] [Quicksort (विडियो)](https://www.youtube.com/watch?v=y_G9BkAm6B8&index=4&list=PL89B61F78B552C1AB)
- [ ] [Selection Sort (विडियो)](https://www.youtube.com/watch?v=6nDMgr0-Yyo&index=8&list=PL89B61F78B552C1AB)

- [ ] Stanford lectures on sorting:
    - [ ] [Lecture 15 | Programming Abstractions (विडियो)](https://www.youtube.com/watch?v=ENp00xylP7c&index=15&list=PLFE6E58F856038C69)
    - [ ] [Lecture 16 | Programming Abstractions (विडियो)](https://www.youtube.com/watch?v=y4M9IVgrVKo&index=16&list=PLFE6E58F856038C69)

- [ ] Shai Simonson, [Aduni.org](http://www.aduni.org/):
    - [ ] [Algorithms - Sorting - Lecture 2 (विडियो)](https://www.youtube.com/watch?v=odNJmw5TOEE&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=2)
    - [ ] [Algorithms - Sorting II - Lecture 3 (विडियो)](https://www.youtube.com/watch?v=hj8YKFTFKEE&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=3)

- [ ] Steven Skiena lectures on sorting:
    - [ ] [lecture begins at 26:46 (विडियो)](https://youtu.be/ute-pmMkyuk?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1600)
    - [ ] [lecture begins at 27:40 (विडियो)](https://www.youtube.com/watch?v=yLvp-pB8mak&index=8&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
    - [ ] [lecture begins at 35:00 (विडियो)](https://www.youtube.com/watch?v=q7K9otnzlfE&index=9&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
    - [ ] [lecture begins at 23:50 (विडियो)](https://www.youtube.com/watch?v=TvqIGu9Iupw&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=10)

- [ ] - Merge sort code:
    - [ ] [Using output array](http://www.cs.yale.edu/homes/aspnes/classes/223/examples/sorting/mergesort.c)
    - [ ] [In-place](https://github.com/jwasham/practice-cpp/blob/master/merge_sort/merge_sort.cc)
- [ ] - Quick sort code:
    - [ ] [Implementation](http://www.cs.yale.edu/homes/aspnes/classes/223/examples/randomization/quick.c)
    - [ ] [Implementation](https://github.com/jwasham/practice-c/blob/master/quick_sort/quick_sort.c)

- [ ] Implement:
    - [ ] 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 curiosity - not required:
    - [ ] [Radix Sort](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#radixSort)
    - [ ] [Radix Sort (विडियो)](https://www.youtube.com/watch?v=xhr26ia4k38)
    - [ ] [Radix Sort, Counting Sort (linear time given constraints) (विडियो)](https://www.youtube.com/watch?v=Nz1KZXbghj8&index=7&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
    - [ ] [Randomization: Matrix Multiply, Quicksort, Freivalds' algorithm (विडियो)](https://www.youtube.com/watch?v=cNB2lADK3_s&index=8&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
    - [ ] [Sorting in Linear Time (विडियो)](https://www.youtube.com/watch?v=pOKy3RZbSws&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf&index=14)

## Graphs

Graphs can be used to represent many problems in computer science, so this section is long, like trees and sorting were.

- Notes from Yegge:
    - There are three basic ways to represent a graph in memory:
        - objects and pointers
        - matrix
        - adjacency list
    - 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.

- [ ] Skiena Lectures - great intro:
    - [ ] [CSE373 2012 - Lecture 11 - Graph Data Structures (विडियो)](https://www.youtube.com/watch?v=OiXxhDrFruw&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=11)
    - [ ] [CSE373 2012 - Lecture 12 - Breadth-First Search (विडियो)](https://www.youtube.com/watch?v=g5vF8jscteo&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=12)
    - [ ] [CSE373 2012 - Lecture 13 - Graph Algorithms (विडियो)](https://www.youtube.com/watch?v=S23W6eTcqdY&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=13)
    - [ ] [CSE373 2012 - Lecture 14 - Graph Algorithms (con't) (विडियो)](https://www.youtube.com/watch?v=WitPBKGV0HY&index=14&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
    - [ ] [CSE373 2012 - Lecture 15 - Graph Algorithms (con't 2) (विडियो)](https://www.youtube.com/watch?v=ia1L30l7OIg&index=15&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
    - [ ] [CSE373 2012 - Lecture 16 - Graph Algorithms (con't 3) (विडियो)](https://www.youtube.com/watch?v=jgDOQq6iWy8&index=16&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)

- [ ] Graphs (review and more):

    - [ ] [6.006 Single-Source Shortest Paths Problem (विडियो)](https://www.youtube.com/watch?v=Aa2sqUhIn-E&index=15&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
    - [ ] [6.006 Dijkstra (विडियो)](https://www.youtube.com/watch?v=2E7MmKv0Y24&index=16&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
    - [ ] [6.006 Bellman-Ford (विडियो)](https://www.youtube.com/watch?v=ozsuci5pIso&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=17)
    - [ ] [6.006 Speeding Up Dijkstra (विडियो)](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 (विडियो)]( 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 (विडियो)]( https://www.youtube.com/watch?v=ufj5_bppBsA&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=7)
    - [ ] [Aduni: Graph Algorithms III: Shortest Path - Lecture 8 (विडियो)](https://www.youtube.com/watch?v=DiedsPsMKXc&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=8)
    - [ ] [Aduni: Graph Alg. IV: Intro to geometric algorithms - Lecture 9 (विडियो)](https://www.youtube.com/watch?v=XIAQRlNkJAw&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=9)
    - [ ] [CS 61B 2014 (starting at 58:09) (विडियो)](https://youtu.be/dgjX4HdMI-Q?list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd&t=3489)
    - [ ] [CS 61B 2014: Weighted graphs (विडियो)](https://www.youtube.com/watch?v=aJjlQCFwylA&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd&index=19)
    - [ ] [Greedy Algorithms: Minimum Spanning Tree (विडियो)](https://www.youtube.com/watch?v=tKwnms5iRBU&index=16&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
    - [ ] [Strongly Connected Components Kosaraju's Algorithm Graph Algorithm (विडियो)](https://www.youtube.com/watch?v=RpgcYiky7uw)

- Full Coursera Course:
    - [ ] [Algorithms on Graphs (विडियो)](https://www.coursera.org/learn/algorithms-on-graphs/home/welcome)

- Yegge: If you get a chance, try to study up on fancier algorithms:
    - [ ] Dijkstra's algorithm - see above - 6.006
    - [ ] A*
        - [ ] [A Search Algorithm](https://en.wikipedia.org/wiki/A*_search_algorithm)
        - [ ] [A* Pathfinding Tutorial (विडियो)](https://www.youtube.com/watch?v=KNXfSOx4eEE)
        - [ ] [A* Pathfinding (E01: algorithm explanation) (विडियो)](https://www.youtube.com/watch?v=-L-WgKMFuhE)

- I'll implement:
    - [ ] DFS with adjacency list (recursive)
    - [ ] DFS with adjacency list (iterative with stack)
    - [ ] DFS with adjacency matrix (recursive)
    - [ ] DFS with adjacency matrix (iterative with stack)
    - [ ] BFS with adjacency list
    - [ ] BFS with adjacency matrix
    - [ ] single-source shortest path (Dijkstra)
    - [ ] minimum spanning tree
    - DFS-based algorithms (see Aduni विडियो above):
        - [ ] check for cycle (needed for topological sort, since we'll check for cycle before starting)
        - [ ] topological sort
        - [ ] count connected components in a graph
        - [ ] list strongly connected components
        - [ ] check for bipartite graph

You'll get more graph practice in Skiena's book (see Books section below) and the interview books

## Even More Knowledge

- ### Recursion
    - [ ] Stanford lectures on recursion & backtracking:
        - [ ] [Lecture 8 | Programming Abstractions (विडियो)](https://www.youtube.com/watch?v=gl3emqCuueQ&list=PLFE6E58F856038C69&index=8)
        - [ ] [Lecture 9 | Programming Abstractions (विडियो)](https://www.youtube.com/watch?v=uFJhEPrbycQ&list=PLFE6E58F856038C69&index=9)
        - [ ] [Lecture 10 | Programming Abstractions (विडियो)](https://www.youtube.com/watch?v=NdF1QDTRkck&index=10&list=PLFE6E58F856038C69)
        - [ ] [Lecture 11 | Programming Abstractions (विडियो)](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?
        - [ ] [What Is Tail Recursion Why Is It So Bad?](https://www.quora.com/What-is-tail-recursion-Why-is-it-so-bad)
        - [ ] [Tail Recursion (विडियो)](https://www.coursera.org/lecture/programming-languages/tail-recursion-YZic1)
 
- ### 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.
    - [ ] विडियो:
        - the Skiena विडियो 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 (विडियो)](https://youtu.be/Qc2ieXRgR0k?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1718)
        - [ ] [Skiena: CSE373 2012 - Lecture 20 - Edit Distance (विडियो)](https://youtu.be/IsmMhMdyeGY?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=2749)
        - [ ] [Skiena: CSE373 2012 - Lecture 21 - Dynamic Programming Examples (विडियो)](https://youtu.be/o0V9eYF4UI8?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=406)
        - [ ] [Skiena: CSE373 2012 - Lecture 22 - Applications of Dynamic Programming (विडियो)](https://www.youtube.com/watch?v=dRbMC1Ltl3A&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=22)
        - [ ] [Simonson: Dynamic Programming 0 (starts at 59:18) (विडियो)](https://youtu.be/J5aJEcOr6Eo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3558)
        - [ ] [Simonson: Dynamic Programming I - Lecture 11 (विडियो)](https://www.youtube.com/watch?v=0EzHjQ_SOeU&index=11&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm)
        - [ ] [Simonson: Dynamic programming II - Lecture 12 (विडियो)](https://www.youtube.com/watch?v=v1qiRwuJU7g&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=12)
        - [ ] List of individual DP problems (each is short):
            [Dynamic Programming (विडियो)](https://www.youtube.com/playlist?list=PLrmLmBdmIlpsHaNTPP_jHHDx_os9ItYXr)
    - [ ] Yale Lecture notes: 
        - [ ] [Dynamic Programming](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#dynamicProgramming)
    - [ ] Coursera:
        - [ ] [The RNA secondary structure problem (विडियो)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/80RrW/the-rna-secondary-structure-problem)
        - [ ] [A dynamic programming algorithm (विडियो)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/PSonq/a-dynamic-programming-algorithm)
        - [ ] [Illustrating the DP algorithm (विडियो)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/oUEK2/illustrating-the-dp-algorithm)
        - [ ] [Running time of the DP algorithm (विडियो)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/nfK2r/running-time-of-the-dp-algorithm)
        - [ ] [DP vs. recursive implementation (विडियो)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/M999a/dp-vs-recursive-implementation)
        - [ ] [Global pairwise sequence alignment (विडियो)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/UZ7o6/global-pairwise-sequence-alignment)
        - [ ] [Local pairwise sequence alignment (विडियो)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/WnNau/local-pairwise-sequence-alignment)

- ### Combinatorics (n choose k) & Probability
    - [ ] [Math Skills: How to find Factorial, Permutation and Combination (Choose) (विडियो)](https://www.youtube.com/watch?v=8RRo6Ti9d0U)
    - [ ] [Make School: Probability (विडियो)](https://www.youtube.com/watch?v=sZkAAk9Wwa4)
    - [ ] [Make School: More Probability and Markov Chains (विडियो)](https://www.youtube.com/watch?v=dNaJg-mLobQ)
    - [ ] खान अकादमी:
        - Course layout:
            - [ ] [Basic Theoretical Probability](https://www.khanacademy.org/math/probability/probability-and-combinatorics-topic)
        - Just the विडियो - 41 (each are simple and each are short):
            - [ ] [Probability Explained (विडियो)](https://www.youtube.com/watch?v=uzkc-qNVoOk&list=PLC58778F28211FA19)

- ### NP, NP-Complete and Approximation Algorithms
    - Know about the most famous classes of NP-complete problems, such as traveling salesman and the knapsack problem,
        and be able to recognize them when an interviewer asks you them in disguise.
    - Know what NP-complete means.
    - [ ] [Computational Complexity (विडियो)](https://www.youtube.com/watch?v=moPtwq_cVH8&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=23)
    - [ ] Simonson:
        - [ ] [Greedy Algs. II & Intro to NP Completeness (विडियो)](https://youtu.be/qcGnJ47Smlo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=2939)
        - [ ] [NP Completeness II & Reductions (विडियो)](https://www.youtube.com/watch?v=e0tGC6ZQdQE&index=16&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm)
        - [ ] [NP Completeness III (विडियो)](https://www.youtube.com/watch?v=fCX1BGT3wjE&index=17&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm)
        - [ ] [NP Completeness IV (विडियो)](https://www.youtube.com/watch?v=NKLDp3Rch3M&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=18)
    - [ ] Skiena:
        - [ ] [CSE373 2012 - Lecture 23 - Introduction to NP-CompletenessNP Completeness IV (विडियो)](https://youtu.be/KiK5TVgXbFg?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1508)
        - [ ] [CSE373 2012 - Lecture 24 - NP-Completeness Proofs (विडियो)](https://www.youtube.com/watch?v=27Al52X3hd4&index=24&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
        - [ ] [CSE373 2012 - Lecture 25 - NP-Completeness Challenge (विडियो)](https://www.youtube.com/watch?v=xCPH4gwIIXM&index=25&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
    - [ ] [Complexity: P, NP, NP-completeness, Reductions (विडियो)](https://www.youtube.com/watch?v=eHZifpgyH_4&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=22)
    - [ ] [Complexity: Approximation Algorithms (विडियो)](https://www.youtube.com/watch?v=MEz1J9wY2iM&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=24)
    - [ ] [Complexity: Fixed-Parameter Algorithms (विडियो)](https://www.youtube.com/watch?v=4q-jmGrmxKs&index=25&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
    - Peter Norvik discusses near-optimal solutions to traveling salesman problem:
        - [Jupyter Notebook](http://nbviewer.jupyter.org/url/norvig.com/ipython/TSP.ipynb)
    - Pages 1048 - 1140 in CLRS if you have it.

- ### Garbage collection
    - [ ] [Compilers (विडियो)](https://www.youtube.com/playlist?list=PLO9y7hOkmmSGTy5z6HZ-W4k2y8WXF7Bff)
    - [ ] [GC in Python (विडियो)](https://www.youtube.com/watch?v=iHVs_HkjdmI)
    - [ ] [Deep Dive Java: Garbage Collection is Good!](https://www.infoq.com/presentations/garbage-collection-benefits)
    - [ ] [Deep Dive Python: Garbage Collection in CPython (विडियो)](https://www.youtube.com/watch?v=P-8Z0-MhdQs&list=PLdzf4Clw0VbOEWOS_sLhT_9zaiQDrS5AR&index=3)

- ### Caches
    - [ ] LRU cache:
        - [ ] [The Magic of LRU Cache (100 Days of Google Dev) (विडियो)](https://www.youtube.com/watch?v=R5ON3iwx78M)
        - [ ] [Implementing LRU (विडियो)](https://www.youtube.com/watch?v=bq6N7Ym81iI)
        - [ ] [LeetCode - 146 LRU Cache (C++) (विडियो)](https://www.youtube.com/watch?v=8-FZRAjR7qU)
    - [ ] CPU cache:
        - [ ] [MIT 6.004 L15: The Memory Hierarchy (विडियो)](https://www.youtube.com/watch?v=vjYF_fAZI5E&list=PLrRW1w6CGAcXbMtDFj205vALOGmiRc82-&index=24)
        - [ ] [MIT 6.004 L16: Cache Issues (विडियो)](https://www.youtube.com/watch?v=ajgC3-pyGlk&index=25&list=PLrRW1w6CGAcXbMtDFj205vALOGmiRc82-)

- ### Processes and Threads
    - [ ] Computer Science 162 - Operating Systems (25 विडियो):
        - for precesses and threads see विडियो 1-11
        - [Operating Systems and System Programming (विडियो)](https://www.youtube.com/playlist?list=PL-XXv-cvA_iBDyz-ba4yDskqMDY6A1w_c)
    - [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
        - CPU activity, interrupts, context switching
        - Modern concurrency constructs with multicore processors
        - 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 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
    - [ ] [threads in C++ (series - 10 विडियो)](https://www.youtube.com/playlist?list=PL5jc9xFGsL8E12so1wlMS0r0hTQoJL74M)
    - [ ] concurrency in Python (विडियो):
        - [ ] [Short series on threads](https://www.youtube.com/playlist?list=PL1H1sBF1VAKVMONJWJkmUh6_p8g4F2oy1)
        - [ ] [Python Threads](https://www.youtube.com/watch?v=Bs7vPNbB9JM)
        - [ ] [Understanding the Python GIL (2010)](https://www.youtube.com/watch?v=Obt-vMVdM8s)
            - [reference](http://www.dabeaz.com/GIL)
        - [ ] [David Beazley - Python Concurrency From the Ground Up: LIVE! - PyCon 2015](https://www.youtube.com/watch?v=MCs5OvhV9S4)
        - [ ] [Keynote David Beazley - Topics of Interest (Python Asyncio)](https://www.youtube.com/watch?v=ZzfHjytDceU)
        - [ ] [Mutex in Python](https://www.youtube.com/watch?v=0zaPs8OtyKY)


    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.

- ### System Design, Scalability, Data Handling
    - Considerations from Yegge:
        - 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**: [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 (विडियो)](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 (विडियो)](https://www.youtube.com/watch?v=srOgpXECblk)
    - [ ] [A plain english introduction to CAP Theorem](http://ksat.me/a-plain-english-introduction-to-cap-theorem/)
    - [ ] Paxos Consensus algorithm: 
        - [short video](https://www.youtube.com/watch?v=s8JqcZtvnsM)
        - [extended video with use case and multi-paxos](https://www.youtube.com/watch?v=JEpsBg0AO6o)
        - [paper](http://research.microsoft.com/en-us/um/people/lamport/pubs/paxos-simple.pdf)
    - [ ] [Consistent Hashing](http://www.tom-e-white.com/2007/11/consistent-hashing.html)
    - [ ] [NoSQL Patterns](http://horicky.blogspot.com/2009/11/nosql-patterns.html)
    - [ ] [Optional: UML 2.0 Series (vido)](https://www.youtube.com/watch?v=OkC7HKtiZC0&list=PLGLfVvz_LVvQ5G-LdJ8RLqe-ndo7QITYc)
    - [ ] OOSE: Software Dev Using UML and Java (21 विडियो): 
        - Can skip this if you have a great grasp of OO and OO design practices.
        - [OOSE: Software Dev Using UML and Java](https://www.youtube.com/playlist?list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO)
    - [ ] SOLID OOP Principles:
        - [ ] [Bob Martin SOLID Principles of Object Oriented and Agile Design (विडियो)](https://www.youtube.com/watch?v=TMuno5RZNeE)
        - [ ] [SOLID Design Patterns in C# (विडियो)](https://www.youtube.com/playlist?list=PL8m4NUhTQU48oiGCSgCP1FiJEcg_xJzyQ)
        - [ ] [SOLID Principles (विडियो)](https://www.youtube.com/playlist?list=PL4CE9F710017EA77A)
        - [ ] 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 for 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)
            - [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 (विडियो)](https://www.youtube.com/watch?v=3CtAfl7aXAQ)
            - [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgOTViYjJhYzMtMzYxMC00MzFjLWJjMzYtOGJiMDc5N2JkYmJi&hl=en)
        - [ ] D -[Dependency Inversion principle](http://www.oodesign.com/dependency-inversion-principle.html) | Reduce the dependency In composition of objects.
            - [Why Is The Dependency Inversion Principle And Why Is It Important](http://stackoverflow.com/questions/62539/what-is-the-dependency-inversion-principle-and-why-is-it-important)
            - [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgMjdlMWIzNGUtZTQ0NC00ZjQ5LTkwYzQtZjRhMDRlNTQ3ZGMz&hl=en)
    - [ ] Scalability:
        - [ ] [Great overview (विडियो)](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)
        - [ ] [पतझड़acies of Distributed Computing Explained](https://pages.cs.wisc.edu/~zuyu/files/पतझड़acies.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 (विडियो)](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 (विडियो)](https://www.youtube.com/watch?v=9nWyWwY2Onc)
        - [ ] [How Google Does Planet-Scale Engineering for Planet-Scale Infra (विडियो)](https://www.youtube.com/watch?v=H4vMcD7zKM0)
        - [ ] [The Importance of Algorithms](https://www.topcoder.com/community/data-science/data-science-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 (2009)](https://www.infoq.com/presentations/Scale-at-Facebook)
        - [ ] [Scale at Facebook (2012), "Building for a Billion Users" (विडियो)](https://www.youtube.com/watch?v=oodS71YtkGU)
        - [ ] [Engineering for the Long Game - Astrid Atkinson Keynote(विडियो)](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 (विडियो)](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)
        - [ ] [Egnyte Architecture: Lessons Learned In Building And Scaling A Multi Petabyte Distributed System](http://highscalability.com/blog/2016/2/15/egnyte-architecture-lessons-learned-in-building-and-scaling.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)
        - [ ] [Does AMP Counter An Existential Threat To Google?](http://highscalability.com/blog/2015/12/14/does-amp-counter-an-existential-threat-to-google.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" (विडियो)](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 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: [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. 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 function to return the top k requests during past time interval]( https://icmi.cs.ucsb.edu/research/tech_reports/reports/2005-23.pdf)
            - [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/)

- ### Papers
    - These are Google papers and well-known papers.
    - Reading all from end to end with full comprehension will likely take more time than you have. I recommend being selective on papers and their sections.
    - [ ] [1978: Communicating Sequential Processes](http://spinroot.com/courses/summer/Papers/hoare_1978.pdf)
        - [implemented in Go](https://godoc.org/github.com/thomas11/csp)
        - [Love classic papers?](https://www.cs.cmu.edu/~crary/819-f09/)
    - [ ] [2003: The Google File System](http://static.googleusercontent.com/media/research.google.com/en//archive/gfs-sosp2003.pdf)
        - replaced by Colossus in 2012
    - [ ] [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?
    - [ ] [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)
    - [ ] [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)

- ### Unicode
    - [ ] [The Absolute Minimum Every Software Developer Absolutely, Positively Must Know About Unicode and Character Sets]( http://www.joelonsoftware.com/articles/Unicode.html)
    - [ ] [What Every Programmer Absolutely, Positively Needs To Know About Encodings And Character Sets To Work With Text](http://kunststube.net/encoding/)

- ### Emacs and vi(m)
    - suggested by Yegge, from an old Amazon recruiting post: Familiarize yourself with a unix-based code editor
    - vi(m):
        - [video](https://www.youtube.com/watch?v=5givLEMcINQ&index=1&list=PL13bz4SHGmRxlZVmWQ9DvXo1fEg4UdGkr)
        - set of 4 (vidoes):
            - [The vi/vim editor - Lesson 1](https://www.youtube.com/watch?v=SI8TeVMX8pk)
            - [The vi/vim editor - Lesson 2](https://www.youtube.com/watch?v=F3OO7ZIOaJE)
            - [The vi/vim editor - Lesson 3](https://www.youtube.com/watch?v=ZYEccA_nMaI)
            - [The vi/vim editor - Lesson 4](https://www.youtube.com/watch?v=1lYD5gwgZIA)
        - [Using Vi Instead of Emacs](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Using_Vi_instead_of_Emacs)
    - emacs:
        - [Basics Emacs Tutorial](https://www.youtube.com/watch?v=hbmV1bnQ-i0)
        - set of 3 (विडियो):
            - [Emacs Tutorial (Beginners) -Part 1- File commands, cut/copy/paste, cursor commands](https://www.youtube.com/watch?v=ujODL7MD04Q)
            - [Emacs Tutorial (Beginners) -Part 2- Buffer management, search, M-x grep and rgrep modes](https://www.youtube.com/watch?v=XWpsRupJ4II)
            - [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 (विडियो)](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)
        - [(maybe) Org Mode In Depth: Managing Structure (विडियो)](https://www.youtube.com/watch?v=nsGYet02bEk)

- ### Unix command line tools
    - suggested by Yegge, from an old Amazon recruiting post. I filled in the list below from good tools.
    - [ ] bash
    - [ ] cat
    - [ ] grep
    - [ ] sed
    - [ ] awk
    - [ ] curl or wget
    - [ ] sort
    - [ ] tr
    - [ ] uniq
    - [ ] [strace](https://en.wikipedia.org/wiki/Strace)
    - [ ] [tcpdump](https://danielmiessler.com/study/tcpdump/)

- ### Testing
    - To cover:
        - how unit testing works
        - what are mock objects
        - what is integration testing
        - what is dependency injection
    - [ ] [Agile Software Testing with James Bach (विडियो)](https://www.youtube.com/watch?v=SAhJf36_u5U)
    - [ ] [Open Lecture by James Bach on Software Testing (विडियो)](https://www.youtube.com/watch?v=ILkT_HV9DVU)
    - [ ] [Steve Freeman - Test-Driven Development (that’s not what we meant) (विडियो)](https://vimeo.com/83960706)
        - [slides](http://gotocon.com/dl/goto-berlin-2013/slides/SteveFreeman_TestDrivenDevelopmentThatsNotWhatWeMeant.pdf)
    - [ ] [TDD is dead. Long live testing.](http://david.heinemeierhansson.com/2014/tdd-is-dead-long-live-testing.html)
    - [ ] [Is TDD dead? (विडियो)](https://www.youtube.com/watch?v=z9quxZsLcfo)
    - [ ] V[ideo series (152 विडियो) - not all are needed (विडियो)](https://www.youtube.com/watch?v=nzJapzxH_rE&list=PLAwxTw4SYaPkWVHeC_8aSIbSxE_NXI76g)
    - [ ] [Test-Driven Web Development with Python](http://www.obeythetestinggoat.com/pages/book.html#toc)
    - [ ] Dependency injection:
        - [ ] [video](https://www.youtube.com/watch?v=IKD2-MAkXyQ)
        - [ ] [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)

- ### Design patterns
    - [ ] [Quick UML review (विडियो)](https://www.youtube.com/watch?v=3cmzqZzwNDM&list=PLGLfVvz_LVvQ5G-LdJ8RLqe-ndo7QITYc&index=3)
    - [ ] Learn these patterns:
        - [ ] strategy
        - [ ] singleton
        - [ ] adapter
        - [ ] prototype
        - [ ] decorator
        - [ ] visitor
        - [ ] factory, abstract factory
        - [ ] facade
        - [ ] observer
        - [ ] proxy
        - [ ] delegate
        - [ ] command
        - [ ] state
        - [ ] memento
        - [ ] iterator
        - [ ] composite
        - [ ] flyweight
    - [ ] [Chapter 6 (Part 1) - Patterns (विडियो)](https://youtu.be/LAP2A80Ajrg?list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO&t=3344)
    - [ ] [Chapter 6 (Part 2) - Abstraction-Occurrence, General Hierarchy, Player-Role, Singleton, Observer, Delegation (विडियो)](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 (विडियो)](https://www.youtube.com/watch?v=7sduBHuex4c&index=13&list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO)
    - [ ] [Series of विडियो (27 विडियो)](https://www.youtube.com/playlist?list=PLF206E906175C7E07)
    - [ ] [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)

- ### Scheduling
    - in an OS, how it works
    - can be gleaned from Operating System विडियो

- ### Implement system routines
    - understand what lies beneath the programming APIs you use
    - can you implement them?

- ### String searching & manipulations
    - [ ] [Search pattern in text (विडियो)](https://www.coursera.org/learn/data-structures/lecture/tAfHI/search-pattern-in-text)
    - [ ] Rabin-Karp (विडियो):
        - [Rabin Karps Algorithm](https://www.coursera.org/learn/data-structures/lecture/c0Qkw/rabin-karps-algorithm)
        - [Table Doubling, Karp-Rabin](https://www.youtube.com/watch?v=BRO7mVIFt08&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=9)
    - [ ] [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)
    - [ ] Knuth-Morris-Pratt (KMP):
        - [Pratt Algorithm](https://en.wikipedia.org/wiki/Knuth%E2%80%93Morris%E2%80%93Pratt_algorithm)
        - [Tutorial: The Knuth-Morris-Pratt (KMP) String Matching Algorithm](https://www.youtube.com/watch?v=2ogqPWJSftE)
    - [ ] Boyer–Moore string search algorithm
        - [Boyer-Moore String Search Algorithm](https://en.wikipedia.org/wiki/Boyer%E2%80%93Moore_string_search_algorithm)
        - [Advanced String Searching Boyer-Moore-Horspool Algorithms (विडियो)](https://www.youtube.com/watch?v=QDZpzctPf10)
    - [ ] [Coursera: Algorithms on Strings](https://www.coursera.org/learn/algorithms-on-strings/home/week/1)

---

## Final Review 

    This section will have shorter विडियो that can you watch pretty quickly to review most of the important concepts.
    It's nice if you want a refresher often.
    (More items will be added here)

#### General:

- [ ] Series of 2-3 minutes short subject विडियो (23 विडियो)
    - [विडियो](https://www.youtube.com/watch?v=r4r1DZcx1cM&list=PLmVb1OknmNJuC5POdcDv5oCS7_OUkDgpj&index=22)
- [ ] Series of 2-5 minutes short subject विडियो - Michael Sambol (18 विडियो):
    - [विडियो](https://www.youtube.com/channel/UCzDJwLWoYCUQowF_nG3m5OQ)

#### Sorts:

- [ ] Merge Sort: https://www.youtube.com/watch?v=GCae1WNvnZM
   

## Books

### Mentioned in Google Coaching

**Read and do exercises:**

- [ ] The Algorithm Design Manual (Skiena)
    - Book (can rent on kindle):
        - [Algorithm Design Manual](http://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1849967202)
    - Half.com is a great resource for textbooks at good prices.
    - 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/)
    - [Errata](http://www3.cs.stonybrook.edu/~skiena/algorist/book/errata)

    Once you've understood everything in the daily plan, and read and done exercises from the the books above,
    read and do exercises from the books below. Then move to coding challenges (further down below)

**Read first:**
- [ ] [Programming Interviews Exposed: Secrets to Landing Your Next Job, 2nd Edition](http://www.wiley.com/WileyCDA/WileyTitle/productCd-047012167X.html)

**Read second (recommended by many, but not in Google coaching docs):**
- [ ] [Cracking the Coding Interview, 6th Edition](http://www.amazon.com/Cracking-Coding-Interview-6th-Programming/dp/0984782850/)
    - If you see people reference "The Google Resume", it was a book replaced by "Cracking the Coding Interview".

### Additional books 

    These were not suggested by Google but I added because I needed the background knowledge

- [ ] C Programming Language, Vol 2
    - [answers to questions](https://github.com/lekkas/c-algorithms)

- [ ] C++ Primer Plus, 6th Edition

- [ ] [The Unix Programming Environment](http://product.half.ebay.com/The-UNIX-Programming-Environment-by-Brian-W-Kernighan-and-Rob-Pike-1983-Other/54385&tg=info)

- [ ] [Programming Pearls](http://www.amazon.com/Programming-Pearls-2nd-Jon-Bentley/dp/0201657880)

- [ ] [Algorithms and Programming: Problems and Solutions](http://www.amazon.com/Algorithms-Programming-Solutions-Alexander-Shen/dp/0817638474)

### If you have time

- [ ] [Introduction to Algorithms](https://www.amazon.com/Introduction-Algorithms-3rd-MIT-Press/dp/0262033844)
    - Half.com is a great resource for textbooks at good prices.
    
- [ ] [Elements of Programming Interviews](https://www.amazon.com/Elements-Programming-Interviews-Insiders-Guide/dp/1479274836)
    - all code is in C++, if you're looking to use C++ in your interview
    - good book on problem solving in general.

## 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.

- [ ] [Great intro (copied from System Design section): Algorithm design:](http://www.hiredintech.com/algorithm-design/)
- [ ] [How to Find a Solution](https://www.topcoder.com/community/data-science/data-science-tutorials/how-to-find-a-solution/)
- [ ] [How to Dissect a Topcoder Problem Statement](https://www.topcoder.com/community/data-science/data-science-tutorials/how-to-dissect-a-topcoder-problem-statement/)
- [ ] [टॉपकोडर्स के लिए गणित](https://www.topcoder.com/community/data-science/data-science-tutorials/mathematics-for-topcoders/)
- [ ] [डायनामिक प्रोग्रामिंग – नौसिखिया से उन्नत](https://www.topcoder.com/community/data-science/data-science-tutorials/dynamic-programming-from-novice-to-advanced/)

- [MIT इंटरव्यू सामग्री](https://courses.csail.mit.edu/iap/interview/materials.php)

    - [लीटकोड](https://leetcode.com/)
    - [टॉप कोडर](https://www.topcoder.com/)
    - [प्रोजेक्ट यूलर (math-focused)](https://projecteuler.net/index.php?section=problems)
    - [कोडवॉर ](http://www.codewars.com)
    - [हैकररैंक](https://www.hackerrank.com/)
    - [कोदिलिटी](https://codility.com/programmers/)
    - [इंटरव्यूकेक](https://www.interviewcake.com/)
    - [इंटरव्यूबिट](https://www.interviewbit.com)

## Once you're closer to the interview

- [ ] Cracking The Coding Interview Set 2 (विडियो):
    - [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)
    - [Ask Me Anything: Gayle Laakmann McDowell (author of Cracking the Coding Interview)](https://www.youtube.com/watch?v=1fqxMuPmGak)

## आपका रिज्यूमे 

- [एक (थोड़ा) कम भयंकर रिज्यूमे करने के लिए दस सुझाव](http://steve-yegge.blogspot.co.uk/2007_09_01_archive.html)
- Great stuff at the back of Cracking The Coding Interview


## इंटरव्यू की सोंच

   निचे दिए गए विषयो के साथ साथ, अपने २० इंटरव्यू प्रश्न तैयार  रखे. हर एक प्रश्न के २-३ जवाब तैयार  रखे. आपने जो हासिल किया हे उसकी कहानी रखे.
    
- आपको ये नौकरी क्यूँ चाहिए?
- आपने कौनसी एक कठिन समस्या हल की हैं?
- आपकी सबसे बड़ी चुनौतियां कोनसी थी?
- आपने देखी हुई सर्वोतम और बुरी संरचनाये?
- किसी मौजूदा गूगल उत्पाद में सुधार के लिए विचार.
- आप अपना काम सर्वोत्तम कैसे कर सकते हो, टीम के साथ या एकेले?
- आपकी कोनसी कुशलता या अनुभव आपके भूमिका में मददगार होंगे?
- आपने [जॉब क्ष / प्रोजेक्ट य] में सबसे ज्यादा किससे आनद मिला? 
- आपकी सबसे बड़ी [जॉब क्ष/ प्रोजेक्ट य] की चुनोती जिसे आपको सामना करना पड़ा?
-  [जॉब क्ष / प्रोजेक्ट य] में से सबसे बड़ा बग?
- आपने [जॉब क्ष / प्रोजेक्ट य] में क्या सिखा?
- [जॉब क्ष / प्रोजेक्ट य] में आप क्या सुधार कर सकते थे/ करना चाहते थे?

## इंटरव्यूअर के लिए प्रश्न रखे 

    मेरे कुछ प्रश्न (मुझे पहले से ही कुछ जवाब पता है पर मैं टीम की राय जानना चाहता हूँ):

- आपकी टीम कितनी बड़ी हैं?
- आपकी डेव साइकिल कैसी हैं? क्या आपको वॉटरफॉल/स्प्रिंट/एजाइल पता हैं?
- क्या काम के पीछे भागना पड़ता हैं? या लचीलापन हैं?
- आपकी टीम मैं निर्णय कैसे लिए जाते हैं?
- हर सप्ताह आपकी कितनी बैठके होती हैं?
- क्या आपका काम का माहौल काम करने मैं मदद करता हैं?
- आप किसपे काम करते हो?
- आपको उसमे क्या पसंद हैं?
- आपका काम जीवन कैसा हैं?

---

---

## Additional Learnings (not required)

    Everything below is my recommendation, not Google's, and you may not have enough time to
    learn, watch or read them all. That's ok. I may not either.

- ### Information theory (विडियो)
    - [ ] [खान अकादमी](https://www.khanacademy.org/computing/computer-science/informationtheory)
    - [ ] 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. 

- ### Parity & Hamming Code (विडियो)
    - [ ] [Intro](https://www.youtube.com/watch?v=q-3BctoUpHE)
    - [ ] [Parity](https://www.youtube.com/watch?v=DdMcAUlxh1M)
    - [ ] Hamming Code:
        - [Error detection](https://www.youtube.com/watch?v=1A_NcXxdoCc)
        - [Error correction](https://www.youtube.com/watch?v=JAMLuxdHH8o)
    - [ ] [Error Checking](https://www.youtube.com/watch?v=wbH2VxzmoZk)

- ### Entropy
    - also see विडियो below
    - make sure to watch information theory विडियो first
    - [ ] [Information Theory, Claude Shannon, Entropy, Redundancy, Data Compression & Bits (विडियो)](https://youtu.be/JnJq3Py0dyM?t=176)

- ### Cryptography
    - also see विडियो below
    - make sure to watch information theory विडियो first
    - [ ] [खान अकादमी 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 विडियो first
    - [ ] कोम्पुतेरफिल(विडियो): 
        - [ ] [Compression](https://www.youtube.com/watch?v=Lto-ajuqW3w)
        - [ ] [Entropy in Compression](https://www.youtube.com/watch?v=M5c_RFKVkko)
        - [ ] [Upside Down Trees (Huffman Trees)](https://www.youtube.com/watch?v=umTbivyJoiI)
        - [ ] [EXTRA BITS/TRITS - Huffman Trees](https://www.youtube.com/watch?v=DV8efuB3h2g)
        - [ ] [Elegant Compression in Text (The LZ 77 Method)](https://www.youtube.com/watch?v=goOa3DGezUA)
        - [ ] [Text Compression Meets Probabilities](https://www.youtube.com/watch?v=cCDCfoHTsaU)
    - [ ] [Compressor Head विडियो](https://www.youtube.com/playlist?list=PLOU2XLYxmsIJGErt5rrCqaSGTMyyqNt2H)
    - [ ] [(optional) Google Developers Live: GZIP is not enough!](https://www.youtube.com/watch?v=whGwm0Lky2s)

- ### नेटवर्किंग (विडियो)
    - [ ] [खान अकादमी](https://www.khanacademy.org/computing/computer-science/internet-intro)
    - [ ] [UDP और TCP: परिवहन प्रोटोकॉल की तुलना](https://www.youtube.com/watch?v=Vdc8TCESIg8)
    - [ ] [TCP/IP और OSI मॉडल के बारे में](https://www.youtube.com/watch?v=e5DEVa9eSN0)
    - [ ] [इंटरनेट के पार पैकेट पारेषण. नेटवर्किंग और TCP/IP टुटोरिअल.](https://www.youtube.com/watch?v=nomyRJehhnM)
    - [ ] [HTTP](https://www.youtube.com/watch?v=WGJrLqtX7As)
    - [ ] [SSL और HTTPS](https://www.youtube.com/watch?v=S2iBR2ZlZf0)
    - [ ] [SSL/TLS](https://www.youtube.com/watch?v=Rp3iZUvXWlM)
    - [ ] [HTTP 2.0](https://www.youtube.com/watch?v=E9FxNzv1Tr8)
    - [ ] [विडियो शृखला(२१ विडियो)](https://www.youtube.com/playlist?list=PLEbnTDJUr_IegfoqO4iPnPYQui46QqT0j)
    - [ ] [Subnetting Demystified - Part 5 CIDR Notation](https://www.youtube.com/watch?v=t5xYI0jzOf4)

- ### Computer Security
    - [MIT (23 विडियो)](https://www.youtube.com/playlist?list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Introduction, Threat Models](https://www.youtube.com/watch?v=GqmQg-cszw4&index=1&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Control Hijacking Attacks](https://www.youtube.com/watch?v=6bwzNg5qQ0o&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=2)
        - [ ] [Buffer Overflow Exploits and Defenses](https://www.youtube.com/watch?v=drQyrzRoRiA&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=3)
        - [ ] [Privilege Separation](https://www.youtube.com/watch?v=6SIJmoE9L9g&index=4&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Capabilities](https://www.youtube.com/watch?v=8VqTSY-11F4&index=5&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Sandboxing Native Code](https://www.youtube.com/watch?v=VEV74hwASeU&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=6)
        - [ ] [Web Security Model](https://www.youtube.com/watch?v=chkFBigodIw&index=7&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Securing Web Applications](https://www.youtube.com/watch?v=EBQIGy1ROLY&index=8&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Symbolic Execution](https://www.youtube.com/watch?v=yRVZPvHYHzw&index=9&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Network Security](https://www.youtube.com/watch?v=SIEVvk3NVuk&index=11&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Network Protocols](https://www.youtube.com/watch?v=QOtA76ga_fY&index=12&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Side-Channel Attacks](https://www.youtube.com/watch?v=PuVMkSEcPiI&index=15&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)

- ### Parallel Programming
    - [ ] [Coursera (Scala)](https://www.coursera.org/learn/parprog1/home/week/1)
    - [ ] [Efficient Python for High Performance Parallel Computing (विडियो)](https://www.youtube.com/watch?v=uY85GkaYzBk)

- ### Messaging, Serialization, and Queueing Systems
    - [ ] [Thrift](https://thrift.apache.org/)
        - [Tutorial](http://thrift-tutorial.readthedocs.io/en/latest/intro.html)
    - [ ] [Protocol Buffers](https://developers.google.com/protocol-buffers/)
        - [Tutorials](https://developers.google.com/protocol-buffers/docs/tutorials)
    - [ ] [gRPC](http://www.grpc.io/)
        - [gRPC 101 for Java Developers (विडियो)](https://www.youtube.com/watch?v=5tmPvSe7xXQ&list=PLcTqM9n_dieN0k1nSeN36Z_ppKnvMJoly&index=1)
    - [ ] [Redis](http://redis.io/)
        - [Tutorial](http://try.redis.io/)
    - [ ] [Amazon SQS (queue)](https://aws.amazon.com/sqs/)
    - [ ] [Amazon SNS (pub-sub)](https://aws.amazon.com/sns/)
    - [ ] [RabbitMQ](https://www.rabbitmq.com/)
        - [Get Startet](https://www.rabbitmq.com/getstarted.html)
    - [ ] [Celery](http://www.celeryproject.org/)
        - [First Steps With Celery](http://docs.celeryproject.org/en/latest/getting-started/first-steps-with-celery.html)
    - [ ] [ZeroMQ](http://zeromq.org/)
        - [Intro - Read The Manual](http://zeromq.org/intro:read-the-manual)
    - [ ] [ActiveMQ](http://activemq.apache.org/)
    - [ ] [Kafka](http://kafka.apache.org/documentation.html#introduction)
    - [ ] [MessagePack](http://msgpack.org/index.html)
    - [ ] [Avro](https://avro.apache.org/)

- ### Fast Fourier Transform
    - [ ] [What is a Fourier transform? What is it used for?](http://www.askamathematician.com/2012/09/q-what-is-a-fourier-transform-what-is-it-used-for/)
    - [ ] [What is the Fourier Transform? (विडियो)](https://www.youtube.com/watch?v=Xxut2PN-V8Q)
    - [ ] [Divide & Conquer: FFT (विडियो)](https://www.youtube.com/watch?v=iTMn0Kt18tg&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=4)
    - [ ] [Understanding The FFT](http://jakevdp.github.io/blog/2013/08/28/understanding-the-fft/)

- ### Bloom Filter
    - Given a Bloom filter with m bits and k hashing functions, both insertion and membership testing are O(k)
    - [Bloom Filters](https://www.youtube.com/watch?v=-SuTGoFYjZs)
    - [Bloom Filters | Mining of Massive Datasets | Stanford University](https://www.youtube.com/watch?v=qBTdukbzc78)
    - [Tutorial](http://billmill.org/bloomfilter-tutorial/)
    - [How To Write A Bloom Filter App](http://blog.michaelschmatz.com/2016/04/11/how-to-write-a-bloom-filter-cpp/)

- ### van Emde Boas Trees
    - [ ] [Divide & Conquer: van Emde Boas Trees (विडियो)](https://www.youtube.com/watch?v=hmReJCupbNU&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=6)
    - [ ] [MIT Lecture Notes](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-design-and-analysis-of-algorithms-spring-2012/lecture-notes/MIT6_046JS12_lec15.pdf)

- ### Augmented Data Structures
    - [ ] [CS 61B Lecture 39: Augmenting Data Structures](https://youtu.be/zksIj9O8_jc?list=PL4BBB74C7D2A1049C&t=950)

- ### Skip lists
    - "These are somewhat of a cult data structure" - Skiena
    - [ ] [Randomization: Skip Lists (विडियो)](https://www.youtube.com/watch?v=2g9OSRKJuzM&index=10&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
    - [ ] [For animations and a little more detail](https://en.wikipedia.org/wiki/Skip_list)

- ### Network Flows
    - [ ] [Ford-Fulkerson in 5 minutes (विडियो)](https://www.youtube.com/watch?v=v1VgJmkEJW0)
    - [ ] [Ford-Fulkerson Algorithm (विडियो)](https://www.youtube.com/watch?v=v1VgJmkEJW0)
    - [ ] [Network Flows (विडियो)](https://www.youtube.com/watch?v=2vhN4Ice5jI)

- ### Disjoint Sets & Union Find
    - [ ] [Disjoint Set](https://en.wikipedia.org/wiki/Disjoint-set_data_structure)
    - [ ] [UCB 61B - Disjoint Sets; Sorting & selection (विडियो)](https://www.youtube.com/watch?v=MAEGXTwmUsI&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd&index=21)
    - [ ] Coursera (not needed since the above video explains it great):
        - [ ] [Overview](https://www.coursera.org/learn/data-structures/lecture/JssSY/overview)
        - [ ] [Naive Implementation](https://www.coursera.org/learn/data-structures/lecture/EM5D0/naive-implementations)
        - [ ] [Trees](https://www.coursera.org/learn/data-structures/lecture/Mxu0w/trees)
        - [ ] [Union By Rank](https://www.coursera.org/learn/data-structures/lecture/qb4c2/union-by-rank)
        - [ ] [Path Compression](https://www.coursera.org/learn/data-structures/lecture/Q9CVI/path-compression)
        - [ ] [Analysis Options](https://www.coursera.org/learn/data-structures/lecture/GQQLN/analysis-optional)

- ### Math for Fast Processing
    - [ ] [Integer Arithmetic, Karatsuba Multiplication (विडियो)](https://www.youtube.com/watch?v=eCaXlAaN2uE&index=11&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
    - [ ] [The Chinese Remainder Theorem (used in cryptography) (विडियो)](https://www.youtube.com/watch?v=ru7mWZJlRQg)
    
- ### Treap
    - Combination of a binary search tree and a heap
    - [ ] [Treap](https://en.wikipedia.org/wiki/Treap)
    - [ ] [Data Structures: Treaps explained (विडियो)](https://www.youtube.com/watch?v=6podLUYinH8)
    - [ ] [Applications in set operations](https://www.cs.cmu.edu/~scandal/papers/treaps-spaa98.pdf)
    
- ### Linear Programming (विडियो)
    - [ ] [Linear Programming](https://www.youtube.com/watch?v=M4K6HYLHREQ)
    - [ ] [Finding minimum cost](https://www.youtube.com/watch?v=2ACJ9ewUC6U)
    - [ ] [Finding maximum value](https://www.youtube.com/watch?v=8AA_81xI3ik)

- ### ज्यामिति, कॉन्वेक्स हल (विडियो)
    - [ ] [लेखाचित्र अल्गोरिथम IV: ज्यामितीय एल्गोरिदम का परिचय - व्याख्यान ९](https://youtu.be/XIAQRlNkJAw?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3164)
    - [ ] [ज्यामितीय एल्गोरिदम: ग्रैहम और जारविस - व्याख्यान १०](https://www.youtube.com/watch?v=J5aJEcOr6Eo&index=10&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm)
    - [ ] [डिवाइड और कॉन्कर: कॉन्वेक्स हल, माध्य ढूँढना](https://www.youtube.com/watch?v=EzeYI7p9MjU&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=2)

- ### Discrete math
    - see विडियो 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 (विडियो)](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 (विडियो)](https://www.youtube.com/watch?v=Ja2hxBAwG_0)
    - [ ] [Google Developers' Machine Learning Recipes (Scikit Learn & Tensorflow) (विडियो)](https://www.youtube.com/playlist?list=PLOU2XLYxmsIIuiBfYad6rFYQU_jL2ryal)
    - [ ] [Tensorflow (विडियो)](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)
              - [विडियो only](https://www.youtube.com/playlist?list=PLZ9qNFMHZ-A4rycgrgOYma6zxF4BZGGPW)
              - see विडियो 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:
        - Great book: Data Science from Scratch: First Principles with Python: https://www.amazon.com/Data-Science-Scratch-Principles-Python/dp/149190142X
        - Data School: http://www.dataschool.io/

- ### गो
    - [ ] विडियो:
        - [ ] [Why Learn Go?](https://www.youtube.com/watch?v=FTl0tl9BGdc)
        - [ ] [Go Programming](https://www.youtube.com/watch?v=CF9S4QZuV30)
        - [ ] [A Tour of Go](https://www.youtube.com/watch?v=ytEkHepK08c)
    - [ ] पुस्तके:
        - [ ] [गो प्रोग्रामिंग का परिचय (ऑनलाइन मुफ्त पढ़े)](https://www.golang-book.com/books/intro)
        - [ ] [गो प्रोग्रामिंग लैंग्वेज (दोनोवन & केर्निघन)](https://www.amazon.com/Programming-Language-Addison-Wesley-Professional-Computing/dp/0134190440)
    - [ ] [बूटकैंप ](https://www.golang-book.com/guides/bootcamp)

--

## 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?

- [ ] **और डायनामिक प्रोग्रामिंग** (विडियो)
    - [ ] [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)
    - [ ] [6.046: 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)

- [ ] **Advanced Graph Processing** (विडियो)
    - [ ] [Synchronous Distributed Algorithms: Symmetry-Breaking. Shortest-Paths Spanning Trees](https://www.youtube.com/watch?v=mUBmcbbJNf4&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=27)
    - [ ] [Asynchronous Distributed Algorithms: Shortest-Paths Spanning Trees](https://www.youtube.com/watch?v=kQ-UQAzcnzA&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=28)

- [ ] MIT **Probability** (mathy, and go slowly, which is good for mathy things) (विडियो):
    - [ ] [MIT 6.042J - Probability Introduction](https://www.youtube.com/watch?v=SmFwFdESMHI&index=18&list=PLB7540DEDD482705B)
    - [ ] [MIT 6.042J - Conditional Probability](https://www.youtube.com/watch?v=E6FbvM-FGZ8&index=19&list=PLB7540DEDD482705B)
    - [ ] [MIT 6.042J - Independence](https://www.youtube.com/watch?v=l1BCv3qqW4A&index=20&list=PLB7540DEDD482705B)
    - [ ] [MIT 6.042J - Random Variables](https://www.youtube.com/watch?v=MOfhhFaQdjw&list=PLB7540DEDD482705B&index=21)
    - [ ] [MIT 6.042J - Expectation I](https://www.youtube.com/watch?v=gGlMSe7uEkA&index=22&list=PLB7540DEDD482705B)
    - [ ] [MIT 6.042J - Expectation II](https://www.youtube.com/watch?v=oI9fMUqgfxY&index=23&list=PLB7540DEDD482705B)
    - [ ] [MIT 6.042J - Large Deviations](https://www.youtube.com/watch?v=q4mwO2qS2z4&index=24&list=PLB7540DEDD482705B)
    - [ ] [MIT 6.042J - Random Walks](https://www.youtube.com/watch?v=56iFMY8QW2k&list=PLB7540DEDD482705B&index=25)

- [ ] [Simonson: Approximation Algorithms (विडियो)](https://www.youtube.com/watch?v=oDniZCmNmNw&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=19)

## Video Series

Sit back and enjoy. "netflix and skill" :P

- [ ] [List of individual Dynamic Programming problems (each is short)](https://www.youtube.com/playlist?list=PLrmLmBdmIlpsHaNTPP_jHHDx_os9ItYXr)

- [ ] [x86 Architecture, Assembly, Applications (11 विडियो)](https://www.youtube.com/playlist?list=PL038BE01D3BAEFDB0)

- [ ] [MIT 18.06 Linear Algebra, वसंत2005 (35 विडियो)](https://www.youtube.com/playlist?list=PLE7DDD91010BC51F8)

- [ ] [Excellent - MIT Calculus Revisited: Single Variable Calculus](https://www.youtube.com/playlist?list=PL3B08AE665AB9002A)

- [ ] [कंप्यूटर विज्ञान ७०, ००१ – वसंत २०१५ - Discrete Mathematics and Probability Theory](https://www.youtube.com/playlist?list=PL-XXv-cvA_iD8wQm8U0gG_Z1uHjImKXFy)

- [ ] [Discrete Mathematics (१९ विडियो)](https://www.youtube.com/playlist?list=PLWX710qNZo_sNlSWRMVIh6kfTjolNaZ8t)

- [ ] CSE373 - एल्गोरिदम का विश्लेषण (२५ विडियो)
    - [एल्गोरिथ्म डिजाइन मैनुअल से Skiena व्याख्यान](https://www.youtube.com/watch?v=ZFjhkohHdAA&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=1)

- [ ] [UC बर्कले 61B (वसंत2014): डेटा संरचनाएं (२५ विडियो)](https://www.youtube.com/watch?v=mFPmKGIrQs4&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd)

- [ ] [UC बर्कले 61B (पतझड़ 2006): डेटा संरचनाएं (३९ विडियो)]( https://www.youtube.com/playlist?list=PL4BBB74C7D2A1049C)

- [ ] [UC बर्कले 61C: मशीन संरचनाएं (२६ विडियो)](https://www.youtube.com/watch?v=gJJeUFyuvvg&list=PL-XXv-cvA_iCl2-D-FS5mk0jFF6cYSJs_)
    
- [ ] [OOSE: युमल और जावा के साथ सॉफ्टवेर का विकास (२१ विडियो)](https://www.youtube.com/playlist?list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO)

- [ ] [UC बर्कले CS १५२: कंप्यूटर वास्तुकला और इंजीनियरिंग (२० विडियो )](https://www.youtube.com/watch?v=UH0QYvtP7Rk&index=20&list=PLkFD6_40KJIwEiwQx1dACXwh-2Fuo32qr)

- [ ] [MIT ६.००४: संगणना संरचनाएं (४९ विडियो)](https://www.youtube.com/playlist?list=PLrRW1w6CGAcXbMtDFj205vALOGmiRc82-)

- [ ] [MIT ६.००६: अल्गोरिथम की पहेचान (४७ विडियो)](https://www.youtube.com/watch?v=HtSuA80QTyo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&nohtml5=False)

- [ ] [MIT ६.०३३: कंप्यूटर सिस्टम इंजीनियरिंग (२२ विडियो)](https://www.youtube.com/watch?v=zm2VP0kHl1M&list=PL6535748F59DCA484)

- [ ] [MIT ६.०३४ कृत्रिम होशियारी, पतझड़ २०१० (३० विडियो)](https://www.youtube.com/playlist?list=PLUl4u3cNGP63gFHB6xb-kVBiQHYe_4hSi)

- [ ] [MIT ६.०४२J: कंप्यूटर विज्ञान के लिए गणित, पतझड़ २०१० (२५ वीडियो)](https://www.youtube.com/watch?v=L3LMbpZIKhQ&list=PLB7540DEDD482705B)

- [ ] [MIT ६.०४६: एल्गोरिदम का विश्लेषण और रचना(३४ विडियो)](https://www.youtube.com/watch?v=2P-yW7LQr08&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)

- [ ] [MIT ६.०५०J: सूचना और एन्ट्रापी, वसंत २००८ (१९ विडियो)](https://www.youtube.com/watch?v=phxsQrZQupo&list=PL_2Bwul6T-A7OldmhGODImZL8KEVE38X7)

- [ ] [MIT ६.८५१: उन्नत डेटा संरचनाएं (२२ विडियो)](https://www.youtube.com/watch?v=T0yzrZL1py0&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf&index=1)

- [ ] [MIT ६.८५४: उन्नत एल्गोरिदम, वसंत २०१६ (२४ विडियो)](https://www.youtube.com/playlist?list=PL6ogFv-ieghdoGKGg2Bik3Gl1glBTEu8c)

- [ ] [MIT ८६.८५८ कंप्यूटर सिस्टम्स सुरक्षा, पताज़द २०१४](https://www.youtube.com/watch?v=GqmQg-cszw4&index=1&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)

- [ ] स्टैनफोर्ड: प्रोग्रामिंग मानदंड (१७ विडियो)
    - [C और C++ पर कोर्स](https://www.youtube.com/watch?v=jTSvthW34GU&list=PLC0B8B318B7394B6F&nohtml5=False)

- [ ] [क्रिप्टोग्राफ़ी का परिचय](https://www.youtube.com/watch?v=2aHkqB2-46k&feature=youtu.be)
    - [श्रृंखला में अधिक (क्रम में नहीं)](https://www.youtube.com/channel/UC1usFRN4LCMcfIV7UjHNuQg)
    
- [ ] [विशाल डेटासेट खनन – स्टैनफोर्ड विश्वविद्यालय(९४ विडियो)](https://www.youtube.com/playlist?list=PLLssT5z_DsK9JDLcT8T62VtzwyW9LNepV)

## शायद

http://www.gainlo.co/#!/ - बड़ी कंपनी के मोक इंटरव्यू

---

## जब आपको नौकरी मिल जाये 

बधाई हो!

- [१० बाते काश मुझे गूगल के पहले दिन पता होती](https://medium.com/@moonstorming/10-things-i-wish-i-knew-on-my-first-day-at-google-107581d87286#.livxn7clw)

सिखाते रहो.

वास्तव में आपकी पढाई कभी ख़त्म नहीं होती.
