> من در ابتدا این لیست رو به عنوان یک لیست کوتاه از مجموعه موضوعات پژوهشی برای تبدیل شدن به یک مهندس نرم افزار ایجاد کردم، اما به فهرست بلند و بالایی که امروز میبینید تبدیل شد.
> بعد از طی کردن این طرح, [به عوان مهندس توسعه نرم افزار در آمازون استخدام شدم](https://startupnextdoor.com/ive-been-acquired-by-amazon/?src=ciu)!
> احتمالاً مجبور نخواهید بود به آن اندازه که من مطالطه کردم مطالعه کنید. به هر حال هر چیزی که نیاز داشته باشید در اینجا ذکر شده
>
> من بین 8 تا 10 ساعت در روز، برای چندین ماه مطالعه کردم. داستان از این قرار است: [چرا 8 ماه تمام وقت برای مصاحبه گوگل مطالعه کردم](https://medium.freecodecamp.org/why-i-studied-full-time-for-8-months-for-a-google-interview-cc662ce9bb13)
>
> **لطفاً توجه داشته باشید:** لازم نیست به اندازه من مطالعه کنید. من زمان زیادی رو برای دانستن چیزهایی که نیازی به دانستن آنها نداشتم تلف کردم. که بیشتر در پایین توضیح میدهم. من به شما کمک میکنم که بدون اتلاف وقت گرانبهای خود به هدف خود برسید.
>
> موارد ذکر شده در اینجا شما را برای یک مصاحبه فنی، تقریباً در هر شرکت نرم افزاری به خوبی آماده می کند,
> از جمله غول ها: آمازون، فیس بوک، گوگل و مایکروسافت
>
> *با آرزوی موفقیت*
<details>
<summary>ترجمه ها:</summary>
- [中文版本](translations/README-cn.md)
- [Tiếng Việt - Vietnamese](translations/README-vi.md)
<sup><strong>Founded in 2018, OSS Capital is the first and only venture capital platform focused<br>exclusively on supporting early-stage COSS (commercial open source) startup founders.</strong></sup>
<strong>Dev environments built for the cloud</strong>
</p>
</div>
<div>
<sup>Natively integrated with GitLab, GitHub, and Bitbucket, Gitpod automatically and continuously prebuilds dev environments for all your branches. As a result team members can instantly start coding with fresh dev environments for each new task - no matter if you are building a new feature, want to fix a bug, or work on a code review.</sup>
</div>
</a>
</p>
<hr/>
</div>
## این چیه؟
![Coding at the whiteboard - from HBO's Silicon Valley](https://d3j2pkmjtin6ou.cloudfront.net/coding-at-the-whiteboard-silicon-valley.png)
این برنامه پژوهشی چند ماهه من جهت تبدیل شدن به یک مهندس نرم افزار برای یک شرکت بزرگ است.
توجه داشته باشید که این یک برنامه مطالعاتی برای **مهندسی نرم افزار** است، نه توسعه وب. شرکت های بزرگ نرم افزاری مانند گوگل، آمازون،
فیس بوک و مایکروسافت مهندسی نرم افزار را متفاوت از توسعه وب می دانند. برای مثال در آمازون مهندسین فرانت اند (FEE) و مهندسان توسعه نرم افزار (SDE) وجود دارند. این دو تا نقش های جداگانه هستند و مصاحبه برای آنها یکسان نخواهد بود، زیرا هر کدام شایستگی های خاص خود را دارند. این شرکت ها برای نقش های توسعه نرم افزار/مهندسی نیاز به دانش علوم کامپیوتر دارند.
</div>
---
## فهرست مطالب
### برنامه مطالعه
- [این چیه؟](#این-چیه)
- [چرا ازش استفاده کنیم؟](#چرا-ازش-استفاده-کنیم)
- [نحوه استفاده](#نحوه-استفاده)
- [احساس نکنید که به اندازه کافی باهوش نیستید](#احساس-نکنید-که-به-اندازه-کافی-باهوش-نیستید)
- [نکته ای درباره منابع ویدئویی](#نکته-ای-درباره-منابع-ویدیویی)
- [یک زبان برنامه نویسی انتخاب کنید](#یک-زبان-برنامه-نویسی-انتخاب-کنید)
- [کتاب های مربوط به ساختمان داده و الگوریتم](#کتاب-های-مربوط-به-ساختمان-داده-و-الگوریتم)
- [جزئیات بیشتر در مورد برخی از موضوعات](#جزئیات-بیشتر-در-مورد-برخی-از-موضوعات)
- [مجموعه ویدیویی](#مجموعه-ویدیویی)
- [دوره های علوم کامپیوتر](#دوره-های-علوم-کامپیوتر)
- [مقالات](#papers)
---
## چرا ازش استفاده کنیم؟
اگر می خواهید به عنوان مهندس نرم افزار برای یک شرکت بزرگ کار کنید، اینها چیزهایی هستند که باید بدانید.
اگر مانند من موفق به دریافت مدرک در رشته علوم کامپیوتر نشدید، این لیست شما رو در میابد و 4 سال از زندگی شما رو حفظ میکند
وقتی این پروژه را شروع کردم فرق بین پشته و هیپ رو نمیدانستم، یا چیزی درمورد پیچیدگی زمانی و درخت ها نمیدانستم , و یا اینکه چگونه یک گراف رو پیمایش کنم. اگر مجبور بودم یک الگوریتم مرتبسازی را کدنویسی کنم، میتوانم به شما بگویم که وحشتناک بود.
هر ساختار داده ای که استفاده میکردم از انواع تعریف شده در زبان برنامه نویسی بود و اصلا از پشت صحنه هیچ خبری نداشتم. من هرگز مجبور نبودم حافظه را مدیریت کنم، مگر اینکه فرآیندی که در حال اجرا بودم،خطای حافظه را نشان دهد, و سپس به فکر این می افتادم که باید یک راه حل پیدا کنم. من تنها قادر بودم از آرایه های چند بعدی استفاده کنم و هرگز یک ساختار داده رو از ابتدا ایجاد نکرده بودم
این یک برنامه طولانی است. ممکن است ماه ها طول بکشد. اگر قبلاً با بسیاری از این موارد آشنا هستید، زمان بسیار کمتری از شما خواهد گرفت.
## نحوه استفاده
موارد را به ترتیب از بالا به پایین بررسی کنید.
من از قابلیت های مارک داون گیتهاب ار جمله قابلیت لیست وظایف برای پیگیری پیشرفت مطالعات استفاده کردم
<divdir="rtl">
**یک برنچ جدید برای تیک زدن مواردی که به اتمام رسانده اید ایجاد کنید، برای این کار فقط یک x داخل براکت قرار دهید : [x]**
</div>
Fork a branch and follow the commands below
این ریپو رو فورک کنید https://github.com/jwasham/coding-interview-university
تمام باکس هایی که به اتمام رسانیده اید را با X علامت بزنید:
</div>
git add .
git commit -m "Marked x"
git rebase jwasham/main
git push --set-upstream origin progress
git push --force
[More about GitHub-flavored markdown](https://guides.github.com/features/mastering-markdown/#GitHub-flavored-markdown)
## احساس نکنید که به اندازه کافی باهوش نیستید
- مهندسان نرم افزار موفق باهوش هستند، اما بسیاری از آنها این حس ناامنی را دارند که به اندازه کافی باهوش نیستند.
- [افسانه برنامه نویس نابغه](https://www.youtube.com/watch?v=0SARbwvhupQ)
- [تنها رفتن خطرناک است: مبارزه با هیولاهای نامرئی در فناوری](https://www.youtube.com/watch?v=1i8ylq4j_EY)
## نکته ای درباره منابع ویدئویی
<divdir="rtl">
برخی از ویدیوها فقط با ثبت نام در کلاس Coursera یا EdX در دسترس هستند. که بهشون دوره های گسترده باز (MOOC) میگویند.
بعضی مواقع کلاس ها در باز های زمانی خاصی دایر میشوند، بنابراین باید چند ماه برای شرکت در این کلاس ها صبر کنید
خیلی عالی میشه که دوره های آنلاین اینچنینی با منابع رایگان و همیشه در دسترس جایگزین بشه,
مانند ویدیوهای یوتیوب (ترجیحاً سخنرانی های دانشگاه)، تا اینکه بتوانید هر زمان که خواستید مطالعه کنید,
نه فقط زمانی که یک دوره آنلاین خاص در حال برگزاری است.
</div>
## یک زبان برنامه نویسی را انتخاب کنید
برای مصاحبه های کدنویسی که انجام می دهید باید یک زبان برنامه نویسی انتخاب کنید.
اما شما همچنین باید زبانی را پیدا کنید که بتوانید از آن برای مطالعه مفاهیم علوم کامپیوتر استفاده کنید.
ترجیحاً زبانهای یکسانی باشند، به طوری که شما فقط باید در یکی از آن ها مهارت داشته باشید.
### برای این طرح مطالعه
<divdir="rtl">
من وقتی داشتم این برنامه مطالعاتی رو انجام میدادم، برای بیشتر آن از دو زبان پایتون و C استفاده میکردم
* C: یک زبان بسیار سطح پایین است. و شما با اشاره گر ها و تخصیص و آزاد سازی حافظه سرو کار دارید, از این رو شما ساختمان داده ها و الگوریتم رو از نزدیک تجربه خواهید کرد. در زبانهای سطح بالاتر مانند پایتون یا جاوا، اینها از شما پنهان هستند. که برای کارهای روزانه فوق العاده هست,
اما زمانی که در حال یادگیری نحوه ساخت این ساختارهای داده سطح پایین هستید, یک حس دیگری است.
- در طول پروسه مطالعه زبان سی رو همه جا خواهید دید در کتاب ها سخنرانی ها و ویدیوها.
- [The C Programming Language, Vol 2](https://www.amazon.com/Programming-Language-Brian-W-Kernighan/dp/0131103628)
- این یک کتاب کوتاه است، اما به شما مهارت خوبی در زبان C می دهد و اگر کمی آن را تمرین کنید، به سرعت به مهارت خواهید رسید. درک C به شما کمک می کند تا نحوه عملکرد برنامه ها و حافظه را درک کنید.
- نیازی نیست خیلی عمیق در این کتاب فرو بروید فقط تا حدی لازم است که بتوانید کد های زبان سی رو بخوانید و بنویسید.
- [پاسخ به سوالات کتاب](https://github.com/lekkas/c-algorithms)
* Python: مدرن و بسیار رسا، من پایتون رو برای اینکه یک زبان بسیار مفید هست یاد گرفتم و همچنین برای اینکه این امکان رو بهم میده که کد کمتری در مصاحبه بنویسم.
این دو زبان ترجیجات من هستند. البته شما میتوانید هر چیزی که دوست دارید انتخاب کنید.
ممکن است لازم نباشه ، ولی در اینجا چند سایت برای یادگیری یک زبان جدید وجود دارد:
- [Data Structures and Algorithms in C++, 2nd Edition](https://www.amazon.com/Data-Structures-Algorithms-Michael-Goodrich/dp/0470383275)
- Sedgewick and Wayne
- [Algorithms in C++, Parts 1-4: Fundamentals, Data Structure, Sorting, Searching](https://www.amazon.com/Algorithms-Parts-1-4-Fundamentals-Structure/dp/0201350882/)
- [Algorithms in C++ Part 5: Graph Algorithms](https://www.amazon.com/Algorithms-Part-Graph-3rd-Pt-5/dp/0201361183/)
## کتاب های آمادگی مصاحبه
<divdir="rtl">
شما نیازی به خریدن تمام این کتاب ها رو ندارید. راستش رابخواهید احتمالاً کتاب "Cracking the Coding Interview" کافی است,
اما من بیشتر گرفتم تا بیشتر تمرین کنم. اما من همیشه بیش از حد انجام می دهم.
</div>
من هر دوی اینها را خریدم. آنها به من تمرین زیادی دادند.
- [Programming Interviews Exposed: Coding Your Way Through the Interview, 4th Edition](https://www.amazon.com/Programming-Interviews-Exposed-Through-Interview/dp/111941847X/)
- پاسخ به زبان C++ و جاوا
- این یک گرم کردن خوب برای Cracking the Coding Interview است
- خیلی سخت نیست بیشتر مشکلات ممکن است ساده تر از چیزی باشد که در مصاحبه می بینید (از آنچه من خوانده ام)
- [Cracking the Coding Interview, 6th Edition](http://www.amazon.com/Cracking-Coding-Interview-6th-Programming/dp/0984782850/)
- پاسخ در جاوا
### اگر وقت اضافی دارید:
Choose one:
- [Elements of Programming Interviews (C++ version)](https://www.amazon.com/Elements-Programming-Interviews-Insiders-Guide/dp/1479274836)
- [Elements of Programming Interviews in Python](https://www.amazon.com/Elements-Programming-Interviews-Python-Insiders/dp/1537713949/)
- [Elements of Programming Interviews (Java version)](https://www.amazon.com/Elements-Programming-Interviews-Java-Insiders/dp/1517435803/)
- [Companion Project - Method Stub and Test Cases for Every Problem in the Book](https://github.com/gardncl/elements-of-programming-interviews)
## اشتباهات من را مرتکب نشوید
این فهرست در طول چندین ماه رشد کرد و از کنترل خارج شد.
در اینجا برخی از اشتباهاتم رو ذکر میکنم تا شما تجربه بهتری داشته باشید. تا ماه ها در زمان خود صرفه جویی کنید.
### 1. شما همه چیز را به خاطر نخواهید آورد
ساعتها ویدیو تماشا کردم و یادداشتبرداری کردم و ماهها بعد چیز زیادی به یاد نمی آوردم. من 3 روز وقت گذاشتم یادداشت هایم را مرور کردم و فلش کارت درست کردم تا بتوانم مرور کنم. من نیازی به این همه دانستن نداشتم.
به خاطر داشته باشید که من زیاده روی کردم و کارت هایی دارم که همه چیز را از زبان اسمبلی و نکات بی اهمیت پایتون گرفته تا یادگیری ماشینی و آمار را پوشش می دهد.
**یک نکته درباره فلش کارت ها:** به محض اینکه تشخیص دادید که جواب یک کارت را میدانید اون رو به عنوان میدانم علامت نزنید. قبل از آن باید کارت را ببینید و چندین بار جواب درست آن را مرور کنید. پس از چند بار تکرار مبحث مورد نظر عمیقاً در ذهن شما ثبت میشود.
بعضی از دانش آموزان یک به مشکل قالب بندی کارت ها برخوردند که با انجام موارد زیر قابل رفع است: open deck, edit card, click cards, select the "styling" radio button, add the member "white-space: pre;" to the card class.
اگر در خانه تخته وایت برد ندارید، یک پد طراحی بزرگ از یک فروشگاه هنری بردارید. می توانید روی مبل بنشینید و تمرین کنید.
در پایین تصویر دفتر سفیدی که استفاده میکردم رو میبینید، خودکار رو برای بهتر شدن تصویر اضافه کردم. اگه با خودکار توی این دفتر بنویسید آرزو میکنید کاش میتوانستید پاک کنید.
- [ ] [Big O Notations (general quick tutorial) (video)](https://www.youtube.com/watch?v=V6mKVRU1evU)
- [ ] [Big O Notation (and Omega and Theta) - best mathematical explanation (video)](https://www.youtube.com/watch?v=ei-A_wy5Yxw&index=2&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN)
- not the whole video, just portions about Node struct and memory allocation
- [ ] Linked List vs Arrays:
- [Core Linked Lists Vs Arrays (video)](https://www.coursera.org/lecture/data-structures-optimizing-performance/core-linked-lists-vs-arrays-rjBs9)
- [In The Real World Linked Lists Vs Arrays (video)](https://www.coursera.org/lecture/data-structures-optimizing-performance/in-the-real-world-lists-vs-arrays-QUaUd)
- [ ] [why you should avoid linked lists (video)](https://www.youtube.com/watch?v=YQs6IC-vgmo)
- [ ] Gotcha: you need pointer to pointer knowledge:
(for when you pass a pointer to a function that may change the address where that pointer points)
This page is just to get a grasp on ptr to ptr. I don't recommend this list traversal style. Readability and maintainability suffer due to cleverness.
- [Pointers to Pointers](https://www.eskimo.com/~scs/cclass/int/sx8.html)
- [ ] Implement (I did with tail pointer & without):
- [ ] 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
- [ ] [Phone Book Problem (video)](https://www.coursera.org/lecture/data-structures/phone-book-problem-NYZZP)
- [ ] distributed hash tables:
- [Instant Uploads And Storage Optimization In Dropbox (video)](https://www.coursera.org/lecture/data-structures/instant-uploads-and-storage-optimization-in-dropbox-DvaIb)
- [ ] [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: &, |, ^, ~, >>, <<
- [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)
- [ ] [Binary search tree - Implementation in C/C++ (video)](https://www.youtube.com/watch?v=COZK7NATh4k&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=28)
- [ ] [BST implementation - memory allocation in stack and heap (video)](https://www.youtube.com/watch?v=hWokyBoo0aI&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=29)
- [ ] [Find min and max element in a binary search tree (video)](https://www.youtube.com/watch?v=Ut90klNN264&index=30&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
- [ ] [Find height of a binary tree (video)](https://www.youtube.com/watch?v=_pnqMz5nrRs&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=31)
- [ ] [Binary tree traversal - breadth-first and depth-first strategies (video)](https://www.youtube.com/watch?v=9RHO6jU--GU&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=32)
- [ ] [Binary tree: Level Order Traversal (video)](https://www.youtube.com/watch?v=86g8jAQug04&index=33&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
- [ ] [Binary tree traversal: Preorder, Inorder, Postorder (video)](https://www.youtube.com/watch?v=gm8DUJJhmY4&index=34&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
- [ ] [Check if a binary tree is binary search tree or not (video)](https://www.youtube.com/watch?v=yEwSGhSsT0U&index=35&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
- [ ] [Delete a node from Binary Search Tree (video)](https://www.youtube.com/watch?v=gcULXE7ViZw&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=36)
- [ ] [Inorder Successor in a binary search tree (video)](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)
- Process resource needs (memory: code, static storage, stack, heap, and also file descriptors, i/o)
- Thread resource needs (shares above (minus stack) with other threads in the same process but each has its own pc, stack counter, registers, and stack)
- Forking is really copy on write (read-only) until the new process writes to memory, then it does a full copy.
- Context switching
- How context switching is initiated by the operating system and underlying hardware?
- [ ] [threads in C++ (series - 10 videos)](https://www.youtube.com/playlist?list=PL5jc9xFGsL8E12so1wlMS0r0hTQoJL74M)
- [ ] [CS 377 Spring '14: Operating Systems from University of Massachusetts](https://www.youtube.com/playlist?list=PLacuG5pysFbDQU8kKxbUh4K5c1iL5_k7k)
- [ ] concurrency in Python (videos):
- [ ] [Short series on threads](https://www.youtube.com/playlist?list=PL1H1sBF1VAKVMONJWJkmUh6_p8g4F2oy1)
- [ ] [3. Character Based Operations](https://www.coursera.org/learn/algorithms-part2/lecture/jwNmV/character-based-operations)
- [ ] [Notes on Data Structures and Programming Techniques](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Tries)
- [ ] Short course videos:
- [ ] [Introduction To Tries (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/08Xyf/core-introduction-to-tries)
- [ ] [Performance Of Tries (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/PvlZW/core-performance-of-tries)
- [ ] [Implementing A Trie (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/DFvd3/core-implementing-a-trie)
- [ ] [The Trie: A Neglected Data Structure](https://www.toptal.com/java/the-trie-a-neglected-data-structure)
- [ ] [TopCoder - Using Tries](https://www.topcoder.com/community/competitive-programming/tutorials/using-tries/)
- [ ] [Stanford Lecture (real world use case) (video)](https://www.youtube.com/watch?v=TJ8SkcUSdbU)
- [ ] [MIT, Advanced Data Structures, Strings (can get pretty obscure about halfway through) (video)](https://www.youtube.com/watch?v=NinWEPPrkDQ&index=16&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf)
- ### Floating Point Numbers
- [ ] simple 8-bit: [Representation of Floating Point Numbers - 1 (video - there is an error in calculations - see video description)](https://www.youtube.com/watch?v=ji3SfClm8TU)
- [ ] [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/)
- ### Endianness
- [ ] [Big And Little Endian](https://web.archive.org/web/20180107141940/http://www.cs.umd.edu:80/class/sum2003/cmsc311/Notes/Data/endian.html)
- [ ] [Big Endian Vs Little Endian (video)](https://www.youtube.com/watch?v=JrNF0KRAlyo)
- [ ] [Big And Little Endian Inside/Out (video)](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.
- ### Networking
- **if you have networking experience or want to be a reliability engineer or operations engineer, expect questions**
- See Resume prep information in the books: "Cracking The Coding Interview" and "Programming Interviews Exposed"
- I don't know how important this is (you can do your own research) but here is an article on making your resume ATS Compliant:
- [How to Create or Check if your Resume is ATS Compliant](https://ayedot.com/97/MiniBlog/Meaning-of-ATS-compliant-resume-and-How-to-create-ATS-Resume-for-Free)
- ["This Is What A GOOD Resume Should Look Like" by Gayle McDowell (author of Cracking the Coding Interview)](https://www.careercup.com/resume),
- Note by the author: "This is for a US-focused resume. CVs for India and other countries have different expectations, although many of the points will be the same."
## Find a Job
- [Sites for Finding Jobs](https://ayedot.com/151/MiniBlog/Top-10-Best-Websites-for-Careers--Jobs)
## Interview Process & General Interview Prep
- [ ] [How to Pass the Engineering Interview in 2021](https://davidbyttow.medium.com/how-to-pass-the-engineering-interview-in-2021-45f1b389a1)
- Learn how to make yourself ready for software engineer interviews from a former Google interviewer.
- [Python for Data Structures, Algorithms, and Interviews (paid course)](https://www.udemy.com/python-for-data-structures-algorithms-and-interviews/):
- A Python centric interview prep course which covers data structures, algorithms, mock interviews and much more.
- [Intro to Data Structures and Algorithms using Python (Udacity free course)](https://www.udacity.com/course/data-structures-and-algorithms-in-python--ud513):
- A free Python centric data structures and algorithms course.
- [Data Structures and Algorithms Nanodegree! (Udacity paid Nanodegree)](https://www.udacity.com/course/data-structures-and-algorithms-nanodegree--nd256):
- Get hands-on practice with over 100 data structures and algorithm exercises and guidance from a dedicated mentor to help prepare you for interviews and on-the-job scenarios.
- [Grokking the Behavioral Interview (Educative free course)](https://www.educative.io/courses/grokking-the-behavioral-interview):
- Many times, it’s not your technical competency that holds you back from landing your dream job, it’s how you perform on the behavioral interview.
Mock Interviews:
- [Gainlo.co: Mock interviewers from big companies](http://www.gainlo.co/) - I used this and it helped me relax for the phone screen and on-site interview
- [Pramp: Mock interviews from/with peers](https://www.pramp.com/) - peer-to-peer model of practice interviews
- [interviewing.io: Practice mock interview with senior engineers](https://interviewing.io) - anonymous algorithmic/systems design interviews with senior engineers from FAANG anonymously
## Be thinking of for when the interview comes
Think of about 20 interview questions you'll get, along with the lines of the items below. Have at least one answer for each.
Have a story, not just data, about something you accomplished.
- Why do you want this job?
- What's a tough problem you've solved?
- Biggest challenges faced?
- Best/worst designs seen?
- Ideas for improving an existing product
- How do you work best, as an individual and as part of a team?
- Which of your skills or experiences would be assets in the role and why?
- What did you most enjoy at [job x / project y]?
- What was the biggest challenge you faced at [job x / project y]?
- What was the hardest bug you faced at [job x / project y]?
- What did you learn at [job x / project y]?
- What would you have done better at [job x / project y]?
- If you find it hard to come up with good answers of these types of interview questions, here are some ideas:
- [General Interview Questions and their Answers](https://ayedot.com/119/MiniBlog/General-Interview-Questions-and-their-Answers-for-Tech-Jobs)
## Have questions for the interviewer
Some of mine (I already may know the answers, but want their opinion or team perspective):
- How large is your team?
- What does your dev cycle look like? Do you do waterfall/sprints/agile?
- Are rushes to deadlines common? Or is there flexibility?
- How are decisions made in your team?
- How many meetings do you have per week?
- Do you feel your work environment helps you concentrate?
- [Head First Design Patterns](https://www.amazon.com/gp/product/0596007124/)
- A gentle introduction to design patterns
- [Design Patterns: Elements of Reusable Object-Oriented Software](https://www.amazon.com/Design-Patterns-Elements-Reusable-Object-Oriented/dp/0201633612)
- [Write Great Code: Volume 1: Understanding the Machine](https://www.amazon.com/Write-Great-Code-Understanding-Machine/dp/1593270038)
- The book was published in 2004, and is somewhat outdated, but it's a terrific resource for understanding a computer in brief
- The author invented [HLA](https://en.wikipedia.org/wiki/High_Level_Assembly), so take mentions and examples in HLA with a grain of salt. Not widely used, but decent examples of what assembly looks like
- These chapters are worth the read to give you a nice foundation:
- Chapter 2 - Numeric Representation
- Chapter 3 - Binary Arithmetic and Bit Operations
- Chapter 4 - Floating-Point Representation
- Chapter 5 - Character Representation
- Chapter 6 - Memory Organization and Access
- Chapter 7 - Composite Data Types and Memory Objects
- Chapter 9 - CPU Architecture
- Chapter 10 - Instruction Set Architecture
- Chapter 11 - Memory Architecture and Organization
- [Introduction to Algorithms](https://www.amazon.com/Introduction-Algorithms-3rd-MIT-Press/dp/0262033844)
- **Important:** Reading this book will only have limited value. This book is a great review of algorithms and data structures, but won't teach you how to write good code. You have to be able to code a decent solution efficiently
- AKA CLR, sometimes CLRS, because Stein was late to the game
- [Computer Architecture, Sixth Edition: A Quantitative Approach](https://www.amazon.com/dp/0128119055)
- For a richer, more up-to-date (2017), but longer treatment
## System Design, Scalability, Data Handling
**You can expect system design questions if you have 4+ years of experience.**
- Scalability and System Design are very large topics with many topics and resources, since
there is a lot to consider when designing a software/hardware system that can scale.
Expect to spend quite a bit of time on this
- Considerations:
- Scalability
- Distill large data sets to single values
- Transform one data set to another
- Handling obscenely large amounts of data
- System design
- features sets
- interfaces
- class hierarchies
- designing a system under certain constraints
- simplicity and robustness
- tradeoffs
- performance analysis and optimization
- [ ]**START HERE**: [The System Design Primer](https://github.com/donnemartin/system-design-primer)
- [ ] [System Design from HiredInTech](http://www.hiredintech.com/system-design/)
- [ ] [How Do I Prepare To Answer Design Questions In A Technical Interview?](https://www.quora.com/How-do-I-prepare-to-answer-design-questions-in-a-technical-interview?redirected_qid=1500023)
- [ ] [8 Things You Need to Know Before a System Design Interview](http://blog.gainlo.co/index.php/2015/10/22/8-things-you-need-to-know-before-system-design-interviews/)
- [ ] [System Design Interview](https://github.com/checkcheckzz/system-design-interview) - There are a lot of resources in this one. Look through the articles and examples. I put some of them below
- [ ] [How to ace a systems design interview](http://www.palantir.com/2011/10/how-to-rock-a-systems-design-interview/)
- [ ] [Numbers Everyone Should Know](http://everythingisdata.wordpress.com/2009/10/17/numbers-everyone-should-know/)
- [ ] [How long does it take to make a context switch?](http://blog.tsunanet.net/2010/11/how-long-does-it-take-to-make-context.html)
- [ ] [Transactions Across Datacenters (video)](https://www.youtube.com/watch?v=srOgpXECblk)
- [ ] [A plain English introduction to CAP Theorem](http://ksat.me/a-plain-english-introduction-to-cap-theorem)
- [ ] [Engineering for the Long Game - Astrid Atkinson Keynote(video)](https://www.youtube.com/watch?v=p0jGmgIrf_M&list=PLRXxvay_m8gqVlExPC5DG3TGWJTaBgqSA&index=4)
- [ ] [7 Years Of YouTube Scalability Lessons In 30 Minutes](http://highscalability.com/blog/2012/3/26/7-years-of-youtube-scalability-lessons-in-30-minutes.html)
- [ ] [How PayPal Scaled To Billions Of Transactions Daily Using Just 8VMs](http://highscalability.com/blog/2016/8/15/how-paypal-scaled-to-billions-of-transactions-daily-using-ju.html)
- [ ] [How to Remove Duplicates in Large Datasets](https://blog.clevertap.com/how-to-remove-duplicates-in-large-datasets/)
- [ ] [A look inside Etsy's scale and engineering culture with Jon Cowie (video)](https://www.youtube.com/watch?v=3vV4YiqKm1o)
- [ ] [What Led Amazon to its Own Microservices Architecture](http://thenewstack.io/led-amazon-microservices-architecture/)
- [ ] [To Compress Or Not To Compress, That Was Uber's Question](https://eng.uber.com/trip-data-squeeze/)
- [ ] [When Should Approximate Query Processing Be Used?](http://highscalability.com/blog/2016/2/25/when-should-approximate-query-processing-be-used.html)
- [ ] [Google's Transition From Single Datacenter, To Failover, To A Native Multihomed Architecture]( http://highscalability.com/blog/2016/2/23/googles-transition-from-single-datacenter-to-failover-to-a-n.html)
- [ ] [The Image Optimization Technology That Serves Millions Of Requests Per Day](http://highscalability.com/blog/2016/6/15/the-image-optimization-technology-that-serves-millions-of-re.html)
- [ ] [Tinder: How Does One Of The Largest Recommendation Engines Decide Who You'll See Next?](http://highscalability.com/blog/2016/1/27/tinder-how-does-one-of-the-largest-recommendation-engines-de.html)
- [ ] [Design Of A Modern Cache](http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html)
- [ ] [Live Video Streaming At Facebook Scale](http://highscalability.com/blog/2016/1/13/live-video-streaming-at-facebook-scale.html)
- [ ] [A Beginner's Guide To Scaling To 11 Million+ Users On Amazon's AWS](http://highscalability.com/blog/2016/1/11/a-beginners-guide-to-scaling-to-11-million-users-on-amazons.html)
- [ ] [A 360 Degree View Of The Entire Netflix Stack](http://highscalability.com/blog/2015/11/9/a-360-degree-view-of-the-entire-netflix-stack.html)
- [ ] [Latency Is Everywhere And It Costs You Sales - How To Crush It](http://highscalability.com/latency-everywhere-and-it-costs-you-sales-how-crush-it)
- [ ] [What Powers Instagram: Hundreds of Instances, Dozens of Technologies](http://instagram-engineering.tumblr.com/post/13649370142/what-powers-instagram-hundreds-of-instances)
- [ ] [Salesforce Architecture - How They Handle 1.3 Billion Transactions A Day](http://highscalability.com/blog/2013/9/23/salesforce-architecture-how-they-handle-13-billion-transacti.html)
- [ ] [ESPN's Architecture At Scale - Operating At 100,000 Duh Nuh Nuhs Per Second](http://highscalability.com/blog/2013/11/4/espns-architecture-at-scale-operating-at-100000-duh-nuh-nuhs.html)
- [ ] See "Messaging, Serialization, and Queueing Systems" way below for info on some of the technologies that can glue services together
- [ ] Twitter:
- [O'Reilly MySQL CE 2011: Jeremy Cole, "Big and Small Data at @Twitter" (video)](https://www.youtube.com/watch?v=5cKTP36HVgI)
- [Timelines at Scale](https://www.infoq.com/presentations/Twitter-Timeline-Scalability)
- For even more, see "Mining Massive Datasets" video series in the [Video Series](#video-series) section
- [ ] Practicing the system design process: Here are some ideas to try working through on paper, each with some documentation on how it was handled in the real world:
- review: [The System Design Primer](https://github.com/donnemartin/system-design-primer)
- [System Design from HiredInTech](http://www.hiredintech.com/system-design/)
- Familiarize yourself with a unix-based code editor
- vi(m):
- [Editing With vim 01 - Installation, Setup, and The Modes (video)](https://www.youtube.com/watch?v=5givLEMcINQ&index=1&list=PL13bz4SHGmRxlZVmWQ9DvXo1fEg4UdGkr)
- [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
- [How To Write A Bloom Filter App](http://blog.michaelschmatz.com/2016/04/11/how-to-write-a-bloom-filter-cpp/)
- ### HyperLogLog
- [How To Count A Billion Distinct Objects Using Only 1.5KB Of Memory](http://highscalability.com/blog/2012/4/5/big-data-counting-how-to-count-a-billion-distinct-objects-us.html)
- ### Locality-Sensitive Hashing
- Used to determine the similarity of documents
- The opposite of MD5 or SHA which are used to determine if 2 documents/strings are exactly the same
- [Simhashing (hopefully) made simple](http://ferd.ca/simhashing-hopefully-made-simple.html)
- ### van Emde Boas Trees
- [Divide & Conquer: van Emde Boas Trees (video)](https://www.youtube.com/watch?v=hmReJCupbNU&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=6)
- [An Introduction To Binary Search And Red Black Tree](https://www.topcoder.com/community/competitive-programming/tutorials/an-introduction-to-binary-search-and-red-black-trees/)
- **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 (video)](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) (video)](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 (video)](https://archive.org/details/ucberkeley_webcast_zqrqYXkth6Q)
- [Bottom Up 234-Trees (video)](https://www.youtube.com/watch?v=DQdMYevEyE4&index=4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
- [Top Down 234-Trees (video)](https://www.youtube.com/watch?v=2679VQ26Fp4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=5)
- **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
- [Geometric Algorithms: Graham & Jarvis - Lecture 10](https://www.youtube.com/watch?v=J5aJEcOr6Eo&index=10&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm)
- [Divide & Conquer: Convex Hull, Median Finding](https://www.youtube.com/watch?v=EzeYI7p9MjU&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=2)
- ### Discrete math
- [Computer Science 70, 001 - Spring 2015 - Discrete Mathematics and Probability Theory](http://www.infocobuild.com/education/audio-video-courses/computer-science/cs70-spring2015-berkeley.html)
- [Discrete Mathematics by Shai Simonson (19 videos)](https://www.youtube.com/playlist?list=PLWX710qNZo_sNlSWRMVIh6kfTjolNaZ8t)
- [Discrete Mathematics By IIT Ropar NPTEL](https://nptel.ac.in/courses/106/106/106106183/)
- ### Machine Learning
- Why ML?
- [How Google Is Remaking Itself As A Machine Learning First Company](https://backchannel.com/how-google-is-remaking-itself-as-a-machine-learning-first-company-ada63defcb70)
- [Large-Scale Deep Learning for Intelligent Computer Systems (video)](https://www.youtube.com/watch?v=QSaZGT4-6EY)
- [Deep Learning and Understandability versus Software Engineering and Verification by Peter Norvig](https://www.youtube.com/watch?v=X769cyzBNVw)
- [Data Science from Scratch: First Principles with Python](https://www.amazon.com/Data-Science-Scratch-Principles-Python/dp/149190142X)
- [Introduction to Machine Learning with Python](https://www.amazon.com/Introduction-Machine-Learning-Python-Scientists/dp/1449369413/)
- [Machine Learning for Software Engineers](https://github.com/ZuzooVn/machine-learning-for-software-engineers)
- Data School: http://www.dataschool.io/
---
## 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?
- **SOLID**
- [ ] [Bob Martin SOLID Principles of Object Oriented and Agile Design (video)](https://www.youtube.com/watch?v=TMuno5RZNeE)
- [ ] S - [Single Responsibility Principle](http://www.oodesign.com/single-responsibility-principle.html) | [Single responsibility to each Object](http://www.javacodegeeks.com/2011/11/solid-single-responsibility-principle.html)
- [ ] O - [Open/Closed Principle](http://www.oodesign.com/open-close-principle.html) | [On production level Objects are ready for extension but not for modification](https://en.wikipedia.org/wiki/Open/closed_principle)
- [ ] L - [Liskov Substitution Principle](http://www.oodesign.com/liskov-s-substitution-principle.html) | [Base Class and Derived class follow ‘IS A’ Principle](http://stackoverflow.com/questions/56860/what-is-the-liskov-substitution-principle)
- [ ] I - [Interface segregation principle](http://www.oodesign.com/interface-segregation-principle.html) | clients should not be forced to implement interfaces they don't use
- [Interface Segregation Principle in 5 minutes (video)](https://www.youtube.com/watch?v=3CtAfl7aXAQ)
- [ ] 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)
- [6.006: DP IV: Guitar Fingering, Tetris, Super Mario Bros.](https://www.youtube.com/watch?v=tp4_UXaVyx8&index=22&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
- [implemented in Go](https://godoc.org/github.com/thomas11/csp)
- [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?
- [2006: Bigtable: A Distributed Storage System for Structured Data](https://static.googleusercontent.com/media/research.google.com/en//archive/bigtable-osdi06.pdf)
- [2006: The Chubby Lock Service for Loosely-Coupled Distributed Systems](https://research.google.com/archive/chubby-osdi06.pdf)
- [2007: Dynamo: Amazon’s Highly Available Key-value Store](http://s3.amazonaws.com/AllThingsDistributed/sosp/amazon-dynamo-sosp2007.pdf)
- The Dynamo paper kicked off the NoSQL revolution
- [2007: What Every Programmer Should Know About Memory (very long, and the author encourages skipping of some sections)](https://www.akkadia.org/drepper/cpumemory.pdf)
- 2012: AddressSanitizer: A Fast Address Sanity Checker:
- [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)