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+# Google Interview University
+*(formerly known as Project 9894)*
+
+### What is it?
+
+This is my multi-month study plan for going from web developer (self-taught, no CS degree) to
+Google software engineer. Don't let that offend you if you are a web developer. I'm speaking
+from my experience, not yours.
+
+    This long list has been extracted and expanded from Google's coaching notes, so these are the things
+    you need to know. There are extras at the bottom, but this is the list. No shortcuts.
+
+## Why use it?
+
+I'm following this plan to prepare for my Google interview. I've been building the web, building
+services, and launching startups since 1997. I have an economics degree, not a CS degree.  I've
+been very successful in my career, but I want to work at Google. I want to progress into larger systems
+and get a real understanding of computer systems, algorithmic efficiency, data structure performance,
+low-level languages, and how it all works. And if you don't know any of it, Google won't hire you.
+
+When I started this I didn't know a stack from a heap, didn't know Big-O anything, anything about trees, or how to
+traverse a graph. If I had to code a sorting algorithm, I can tell ya it wouldn't have been very good.
+Every data structure I've ever used was built in to the language, and I didn't know how they worked
+under the hood at all. I've never had to manage memory, unless a process I was running would give an "out of
+memory" error, and then I'd have to find a workaround. I've used a few multi-dimensional arrays in my life and
+thousands of associative arrays, but I've never created data structures from scratch.
+
+But after going through this study plan I have high confidence I'll be hired. It's a long plan. It's going to take me
+months. If you are familiar with a lot of this already it will take you a lot less time.
+
+### How to use it
+
+Everything below is an outline, and you should tackle the items in order from top to bottom.
+
+I'm using Github's special markdown flavor, including tasks lists to check my progress.
+
+I check each task box at the beginning of a line when I'm done with it. When all sub-items in a block are done,
+I put [x] at the top level, meaning the entire block is done. Sorry you have to remove all my [x] markings
+to use this the same way. If you search/replace, just replace [x] with [ ].
+Sometimes I just put a [x] at top level if I know I've done all the subtasks, to cut down on clutter.
+
+More about Github flavored markdown: https://guides.github.com/features/mastering-markdown/#GitHub-flavored-markdown
+
+    I have a friendly referral already to get my resume in at Google. Thanks JP.
+
+## Get in a Googley Mood
+
+Print out a "[future Googler](https://github.com/jwasham/project-9894/blob/master/future-googler.pdf)" sign (or two) and keep your eyes on the prize.
+
+## Interview Process & General Interview Prep
+
+- [x] Videos:
+    - [x] https://www.youtube.com/watch?v=oWbUtlUhwa8&feature=youtu.be
+    - [x] https://www.youtube.com/watch?v=qc1owf2-220&feature=youtu.be
+    - [x] https://www.youtube.com/watch?v=8npJLXkcmu8
+
+- [x] Articles:
+    - [x] http://www.google.com/about/careers/lifeatgoogle/hiringprocess/
+    - [x] http://steve-yegge.blogspot.com/2008/03/get-that-job-at-google.html
+        - all the things he mentions that you need to know are listed below
+    - [x] (very dated) http://dondodge.typepad.com/the_next_big_thing/2010/09/how-to-get-a-job-at-google-interview-questions-hiring-process.html
+    - [x] http://sites.google.com/site/steveyegge2/five-essential-phone-screen-questions
+
+- [x] Additional (not suggested by Google but I added):
+    - [x] https://medium.com/always-be-coding/abc-always-be-coding-d5f8051afce2#.4heg8zvm4
+    - [x] https://medium.com/always-be-coding/four-steps-to-google-without-a-degree-8f381aa6bd5e#.asalo1vfx
+    - [x] https://medium.com/@dpup/whiteboarding-4df873dbba2e#.hf6jn45g1
+    - [x] http://www.kpcb.com/blog/lessons-learned-how-google-thinks-about-hiring-management-and-culture
+    - [x] http://www.coderust.com/blog/2014/04/10/effective-whiteboarding-during-programming-interviews/
+    - [x] Cracking The Coding Interview Set 1:
+        - [x] https://www.youtube.com/watch?v=rEJzOhC5ZtQ
+        - [x] https://www.youtube.com/watch?v=aClxtDcdpsQ
+    - [x] How to Get a Job at the Big 4:
+        - [x] https://www.youtube.com/watch?v=YJZCUhxNCv8
+    - [x] http://alexbowe.com/failing-at-google-interviews/
+
+
+## Prerequisite Knowledge
+
+This short section were prerequisites/interesting info I wanted to learn before getting started on the daily plan.
+
+You need to know C, C++, or Java to do the coding part of the interview.
+They will sometimes make an exception and let you use Python or some other language, but the language
+must be mainstream and allow you write your code low-level enough to solve the problems.
+You'll see some C, C++ learning included below.
+
+There are a few books involved, see the bottom.
+
+Some videos are available only by enrolling in a Coursera or EdX class. It is free to do so.
+
+- [x] **How computers process a program:**
+    - [x] https://www.youtube.com/watch?v=42KTvGYQYnA
+    - [x] https://www.youtube.com/watch?v=Mv2XQgpbTNE
+
+- [x] **How floating point numbers are stored:**
+    - [x] simple 8-bit: http://math.stackexchange.com/questions/301435/fractions-in-binary
+    - [x] 32 bit: https://www.youtube.com/watch?v=ji3SfClm8TU
+    - [x] 64 bit: https://www.youtube.com/watch?v=50ZYcZebIec
+
+- [x] **Computer Arch Intro:**
+    (first video only - interesting but not required) https://www.youtube.com/watch?v=zLP_X4wyHbY&list=PL5PHm2jkkXmi5CxxI7b3JCL1TWybTDtKq&index=1
+
+- [x] **C**
+    - [x] K&R C book (ANSI C)
+    - [x] Clang: https://www.youtube.com/watch?v=U3zCxnj2w8M
+    - [x] GDB:
+        - https://www.youtube.com/watch?v=USPvePv1uzE
+        - https://www.youtube.com/watch?v=y5JmQItfFck
+      - Valgrind: https://www.youtube.com/watch?v=fvTsFjDuag8
+- [x] **C++**
+    - [x] basics
+    - [x] pointers
+    - [x] functions
+    - [x] references
+    - [x] templates
+    - [x] compilation
+    - [x] scope & linkage
+    - [x] namespaces
+    - [x] OOP
+    - [x] STL
+    - [x] functors: http://www.cprogramming.com/tutorial/functors-function-objects-in-c++.html
+    - [x] C++ at Google: https://www.youtube.com/watch?v=NOCElcMcFik
+    - [x] Google C++ Style Guide: https://google.github.io/styleguide/cppguide.html
+        - [x] Google uses clang-format (there is a command line "style" argument: -style=google)
+    - [x] Efficiency with Algorithms, Performance with Data Structures: https://youtu.be/fHNmRkzxHWs
+    - [x] review of C++ concepts: https://www.youtube.com/watch?v=Rub-JsjMhWY
+
+- **Python**
+    - I've already use Python quite a bit. This is just for review.
+    - [ ] https://www.youtube.com/watch?v=N4mEzFDjqtA
+
+- [x] **Compilers**
+    - [x] https://class.coursera.org/compilers-004/lecture/1
+    - [x] https://class.coursera.org/compilers-004/lecture/2
+    - [x] C++: https://www.youtube.com/watch?v=twodd1KFfGk
+    - [x] Understanding Compiler Optimization (C++): https://www.youtube.com/watch?v=FnGCDLhaxKU
+
+
+## The Daily Plan:
+
+Each subject does not require a whole day to be able to understand it fully, and you can do multiple of these in a day.
+
+Each day I take one subject from the list below, watch videos about that subject, and write an implementation in:
+    C - using structs and functions that take a struct * and something else as args.
+    C++ - without using built-in types
+    C++ - using built-in types, like STL's std::list for a linked list
+    Python - using built-in types (to keep practicing Python)
+    and write tests to ensure I'm doing it right, sometimes just using simple assert() statements
+    You may do Java or something else, this is just my thing.
+
+Why code in all of these?
+    Practice, practice, practice, until I'm sick of it, and can do it with no problem (some have many edge cases and bookkeeping details to remember)
+    Work within the raw constraints (allocating/freeing memory without help of garbage collection (except Python))
+    Make use of built-in types so I have experience using the built-in tools for real-world use (not going to write my own linked list implementation in production)
+
+I may not have time to do all of these for every subject, but I'll try.
+
+You don't need to memorize the guts of every algorithm.
+
+Write code on a whiteboard, not a computer. Test with some sample inputs.
+Then test it out on a computer to make sure it's not buggy from syntax.
+
+
+- [x] **Before you get started:**
+    - The myth of the Genius Programmer: https://www.youtube.com/watch?v=0SARbwvhupQ
+    - Google engineers are smart, but many have an insecurity that they aren't smart enough.
+
+- [x] **Algorithmic complexity / Big O / Asymptotic analysis**
+    - nothing to implement
+    - Harvard CS50 - Asymptotic Notation: https://www.youtube.com/watch?v=iOq5kSKqeR4
+    - Big O Notations (general quick tutorial) - https://www.youtube.com/watch?v=V6mKVRU1evU
+    - Big O Notation (and Omega and Theta) - best mathematical explanation:
+        - https://www.youtube.com/watch?v=ei-A_wy5Yxw&index=2&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN
+    - Skiena:
+        - video: https://www.youtube.com/watch?v=gSyDMtdPNpU&index=2&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b
+        - slides: http://www3.cs.stonybrook.edu/~algorith/video-lectures/2007/lecture2.pdf
+    - A Gentle Introduction to Algorithm Complexity Analysis: http://discrete.gr/complexity/
+    - Orders of Growth: https://class.coursera.org/algorithmicthink1-004/lecture/59
+    - Asymptotics: https://class.coursera.org/algorithmicthink1-004/lecture/61
+    - UC Berkeley Big O: https://youtu.be/VIS4YDpuP98
+    - UC Berkeley Big Omega: https://youtu.be/ca3e7UVmeUc
+    - Amortized Analysis: https://www.youtube.com/watch?v=B3SpQZaAZP4&index=10&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN
+    - Illustrating "Big O": https://class.coursera.org/algorithmicthink1-004/lecture/63
+    - Cheat sheet: http://bigocheatsheet.com/
+
+## Data Structures
+
+- [x] **Arrays: (Implement an automatically resizing vector)**
+    - [x] Description:
+        - Arrays: https://www.coursera.org/learn/data-structures/lecture/OsBSF/arrays
+        - Arrays: https://www.lynda.com/Developer-Programming-Foundations-tutorials/Basic-arrays/149042/177104-4.html
+        - Multi-dim: https://www.lynda.com/Developer-Programming-Foundations-tutorials/Multidimensional-arrays/149042/177105-4.html
+        - Dynamic Arrays: https://www.coursera.org/learn/data-structures/lecture/EwbnV/dynamic-arrays
+        - Jagged: https://www.lynda.com/Developer-Programming-Foundations-tutorials/Jagged-arrays/149042/177106-4.html
+        - Resizing arrays:
+            - https://class.coursera.org/algs4partI-010/lecture/19
+            - https://www.lynda.com/Developer-Programming-Foundations-tutorials/Resizable-arrays/149042/177108-4.html
+    - [x] Implement a vector (mutable array with automatic resizing):
+        - [x] Practice coding using arrays and pointers, and pointer math to jump to an index instead of using indexing.
+        - [x] 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
+        - [x] size() - number of items
+        - [x] capacity() - number of items it can hold
+        - [x] is_empty()
+        - [x] at(index) - returns item at given index, blows up if index out of bounds
+        - [x] push(item)
+        - [x] insert(index, item) - inserts item at index, shifts that index's value and trailing elements to the right
+        - [x] prepend(item) - can use insert above at index 0
+        - [x] pop() - remove from end, return value
+        - [x] delete(index) - delete item at index, shifting all trailing elements left
+        - [x] remove(item) - looks for value and removes index holding it (even if in multiple places)
+        - [x] find(item) - looks for value and returns first index with that value, -1 if not found
+        - [x] 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
+    - [x] Time
+        - O(1) to add/remove at end (amortized for allocations for more space), index, or update
+        - O(n) to insert/remove elsewhere
+    - [x] 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)
+
+- [x] **Linked Lists**
+    - [x] Description:
+        - [x] https://www.coursera.org/learn/data-structures/lecture/kHhgK/singly-linked-lists
+        - [x] Lynda.com:
+            - https://www.lynda.com/Developer-Programming-Foundations-tutorials/Introduction-lists/149042/177115-4.html
+            - https://www.lynda.com/Developer-Programming-Foundations-tutorials/Understanding-basic-list-implementations/149042/177116-4.html
+            - https://www.lynda.com/Developer-Programming-Foundations-tutorials/Using-singly-doubly-linked-lists/149042/177117-4.html
+            - https://www.lynda.com/Developer-Programming-Foundations-tutorials/List-support-across-languages/149042/177118-4.html
+    - [x] C Code: https://www.youtube.com/watch?v=QN6FPiD0Gzo
+            - not the whole video, just portions about Node struct and memory allocation.
+    - [x] Linked List vs Arrays:
+        - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/rjBs9/core-linked-lists-vs-arrays
+        - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/QUaUd/in-the-real-world-lists-vs-arrays
+    - [x] why you should avoid linked lists:
+        - https://www.youtube.com/watch?v=YQs6IC-vgmo
+    - [x] 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.
+        - https://www.eskimo.com/~scs/cclass/int/sx8.html
+    - [x] implement (I did with tail pointer & without):
+        - [x] size() - returns number of data elements in list
+        - [x] empty() - bool returns true if empty
+        - [x] value_at(index) - returns the value of the nth item (starting at 0 for first)
+        - [x] push_front(value) - adds an item to the front of the list
+        - [x] pop_front() - remove front item and return its value
+        - [x] push_back(value) - adds an item at the end
+        - [x] pop_back() - removes end item and returns its value
+        - [x] front() - get value of front item
+        - [x] back() - get value of end item
+        - [x] insert(index, value) - insert value at index, so current item at that index is pointed to by new item at index
+        - [x] erase(index) - removes node at given index
+        - [x] value_n_from_end(n) - returns the value of the node at nth position from the end of the list
+        - [x] reverse() - reverses the list
+        - [x] remove_value(value) - removes the first item in the list with this value
+    - [x] Doubly-linked List
+        - Description: https://www.coursera.org/learn/data-structures/lecture/jpGKD/doubly-linked-lists
+        - No need to implement
+
+- [x] **Stack**
+    - [x] https://www.coursera.org/learn/data-structures/lecture/UdKzQ/stacks
+    - [x] https://class.coursera.org/algs4partI-010/lecture/18
+    - [x] https://class.coursera.org/algs4partI-010/lecture/19
+    - [x] https://www.lynda.com/Developer-Programming-Foundations-tutorials/Using-stacks-last-first-out/149042/177120-4.html
+    - [x] Will not implement. Implementing with array is trivial.
+
+- [x] **Queue**
+    - [x] https://www.lynda.com/Developer-Programming-Foundations-tutorials/Using-queues-first-first-out/149042/177122-4.html
+    - [x] https://class.coursera.org/algs4partI-010/lecture/20
+    - [x] https://www.coursera.org/learn/data-structures/lecture/EShpq/queue
+    - [x] Circular buffer/FIFO: https://en.wikipedia.org/wiki/Circular_buffer
+    - [x] https://class.coursera.org/algs4partI-010/lecture/23
+    - [x] https://www.lynda.com/Developer-Programming-Foundations-tutorials/Priority-queues-deques/149042/177123-4.html
+    - [x] 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()
+    - [x] 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()
+    - [x] 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)
+
+- [x] **Hash table**
+    - [x] https://www.lynda.com/Developer-Programming-Foundations-tutorials/Understanding-hash-functions/149042/177126-4.html
+    - [x] https://www.lynda.com/Developer-Programming-Foundations-tutorials/Using-hash-tables/149042/177127-4.html
+    - [x] https://www.lynda.com/Developer-Programming-Foundations-tutorials/Supporting-hashing/149042/177128-4.html
+    - [x] https://www.lynda.com/Developer-Programming-Foundations-tutorials/Language-support-hash-tables/149042/177129-4.html
+    - [x] https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/m7UuP/core-hash-tables
+    - [x] https://www.youtube.com/watch?v=C4Kc8xzcA68
+    - [x] https://class.coursera.org/algs4partI-010/lecture/52
+    - [x] https://class.coursera.org/algs4partI-010/lecture/53
+    - [x] https://class.coursera.org/algs4partI-010/lecture/55
+    - [x] https://class.coursera.org/algs4partI-010/lecture/56
+    - [x] https://www.coursera.org/learn/data-structures/home/week/3
+    - [x] https://www.coursera.org/learn/data-structures/lecture/NYZZP/phone-book-problem
+    - [x] distributed hash tables:
+        - https://www.coursera.org/learn/data-structures/lecture/DvaIb/instant-uploads-and-storage-optimization-in-dropbox
+        - https://www.coursera.org/learn/data-structures/lecture/tvH8H/distributed-hash-tables
+    - [x] MIT:
+        - https://www.youtube.com/watch?v=0M_kIqhwbFo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=8
+        - https://www.youtube.com/watch?v=BRO7mVIFt08&index=9&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb
+        - https://www.youtube.com/watch?v=rvdJDijO2Ro&index=10&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb
+    - [x] 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
+
+- [x] **Binary search:**
+    - [x] https://www.youtube.com/watch?v=D5SrAga1pno
+    - [x] https://www.khanacademy.org/computing/computer-science/algorithms/binary-search/a/binary-search
+    - [x] detail: https://www.topcoder.com/community/data-science/data-science-tutorials/binary-search/
+    - [x] Implement:
+        - binary search (on sorted array of integers)
+        - binary search using recursion
+
+- [x] **Bitwise operations**
+    - [x] Get a really good understanding of manipulating bits with: &, |, ^, ~, >>, <<
+        - [x] words: https://en.wikipedia.org/wiki/Word_(computer_architecture)
+        - [x] Good intro:
+            https://www.youtube.com/watch?v=7jkIUgLC29I
+        - [x] https://www.youtube.com/watch?v=d0AwjSpNXR0
+        - [x] https://en.wikipedia.org/wiki/Bit_manipulation
+        - [x] https://en.wikipedia.org/wiki/Bitwise_operation
+        - [x] https://graphics.stanford.edu/~seander/bithacks.html
+        - [x] http://bits.stephan-brumme.com/
+        - [x] http://bits.stephan-brumme.com/interactive.html
+    - [x] 2s and 1s complement
+        - https://www.youtube.com/watch?v=lKTsv6iVxV4
+        - https://en.wikipedia.org/wiki/Ones%27_complement
+        - https://en.wikipedia.org/wiki/Two%27s_complement
+    - [x] count set bits
+        - https://youtu.be/Hzuzo9NJrlc
+        - https://graphics.stanford.edu/~seander/bithacks.html#CountBitsSetKernighan
+        - http://stackoverflow.com/questions/109023/how-to-count-the-number-of-set-bits-in-a-32-bit-integer
+    - [x] round to next power of 2:
+        - http://bits.stephan-brumme.com/roundUpToNextPowerOfTwo.html
+    - [x] swap values:
+        - http://bits.stephan-brumme.com/swap.html
+    - [x] absolute value:
+        - http://bits.stephan-brumme.com/absInteger.html
+
+- [x] **Parity & Hamming Code**
+    - [x] Parity:
+        - https://www.youtube.com/watch?v=DdMcAUlxh1M
+    - [x] Hamming Code:
+        - Error detection: https://www.youtube.com/watch?v=1A_NcXxdoCc
+        - Error correction: https://www.youtube.com/watch?v=JAMLuxdHH8o
+    - [x] Error Checking:
+        - https://www.youtube.com/watch?v=wbH2VxzmoZk
+
+## Trees
+
+- [x] Notes & Background:
+    - [x] Series: https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/ovovP/core-trees
+    - [x] Series: https://www.coursera.org/learn/data-structures/lecture/95qda/trees
+    - basic tree construction
+    - traversal
+    - manipulation algorithms
+    - BFS (breadth-first search)
+        - MIT: 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: 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)
+
+- [x] **Binary search trees: BSTs**
+    - [x] Series: https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/p82sw/core-introduction-to-binary-search-trees
+    - [x] Series: https://class.coursera.org/algs4partI-010/lecture/43
+        - starts with symbol table and goes through BST applications
+    - [x] https://www.coursera.org/learn/data-structures/lecture/E7cXP/introduction
+    - [x] MIT: https://www.youtube.com/watch?v=9Jry5-82I68
+    - C/C++:
+        - [x] https://www.youtube.com/watch?v=COZK7NATh4k&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=28
+        - [x] https://www.youtube.com/watch?v=hWokyBoo0aI&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=29
+        - [x] https://www.youtube.com/watch?v=Ut90klNN264&index=30&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P
+        - [x] https://www.youtube.com/watch?v=_pnqMz5nrRs&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=31
+        - [x] https://www.youtube.com/watch?v=9RHO6jU--GU&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=32
+        - [x] https://www.youtube.com/watch?v=86g8jAQug04&index=33&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P
+        - [x] https://www.youtube.com/watch?v=gm8DUJJhmY4&index=34&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P
+        - [x] https://www.youtube.com/watch?v=yEwSGhSsT0U&index=35&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P
+        - [x] https://www.youtube.com/watch?v=gcULXE7ViZw&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=36
+        - [x] https://www.youtube.com/watch?v=5cPbNCrdotA&index=37&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P
+
+- [x] **Balanced binary trees**
+    - Know least one type of balanced binary tree (and know how it's implemented):
+
+    - [x] **AVL trees**
+        -[x] MIT: https://www.youtube.com/watch?v=FNeL18KsWPc&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=6
+        -[x] https://www.coursera.org/learn/data-structures/lecture/Qq5E0/avl-trees
+        -[x] https://www.coursera.org/learn/data-structures/lecture/PKEBC/avl-tree-implementation
+        -[x] https://www.coursera.org/learn/data-structures/lecture/22BgE/split-and-merge
+
+    - [ ] **red/black trees**
+        - https://class.coursera.org/algs4partI-010/lecture/50
+
+    - [ ] **splay trees**
+        - https://www.coursera.org/learn/data-structures/lecture/O9nZ6/splay-trees
+        - UCB: https://www.youtube.com/watch?v=G5QIXywcJlY
+        - https://www.youtube.com/watch?v=QnPl_Y6EqMo
+
+    - [ ] **B-Trees**
+        - fun fact: B could stand for Boeing, Balanced, or Bayer (co-inventor)
+        - https://en.wikipedia.org/wiki/B-tree
+        - https://class.coursera.org/algs4partI-010/lecture/51
+
+    - [ ] **2-3 search trees**
+        - 2-3 and B-trees: https://class.coursera.org/algs4partI-010/lecture/49
+        - https://www.youtube.com/watch?v=TOb1tuEZ2X4&index=5&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp
+
+- [ ] **N-ary trees**
+    - https://en.wikipedia.org/wiki/K-ary_tree
+
+- [ ] **Tries**
+    - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/08Xyf/core-introduction-to-tries
+    - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/PvlZW/core-performance-of-tries
+    - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/DFvd3/core-implementing-a-trie
+
+- [ ] **Heap (data structure):**
+    - https://en.wikipedia.org/wiki/Heap_(data_structure)
+    - https://www.coursera.org/learn/data-structures/lecture/2OpTs/introduction
+    - https://www.coursera.org/learn/data-structures/lecture/z3l9N/naive-implementations
+    - https://www.coursera.org/learn/data-structures/lecture/GRV2q/binary-trees
+    - https://www.coursera.org/learn/data-structures/supplement/S5xxz/tree-height-remark
+    - https://www.coursera.org/learn/data-structures/lecture/0g1dl/basic-operations
+    - https://www.coursera.org/learn/data-structures/lecture/gl5Ni/complete-binary-trees
+    - https://www.coursera.org/learn/data-structures/lecture/HxQo9/pseudocode
+    - see: https://class.coursera.org/algs4partI-010/lecture
+    - https://class.coursera.org/algs4partI-010/lecture/39
+
+- [ ] **Binary Heap:**
+    Min Heap / Max Heap
+
+- [ ] **Disjoint Sets:**
+    - UCB: https://www.youtube.com/watch?v=wSPAjGfDl7Q&list=PL4BBB74C7D2A1049C&index=31
+    - https://www.coursera.org/learn/data-structures/lecture/JssSY/overview
+    - https://www.coursera.org/learn/data-structures/lecture/EM5D0/naive-implementations
+    - https://www.coursera.org/learn/data-structures/lecture/Mxu0w/trees
+    - https://www.coursera.org/learn/data-structures/lecture/qb4c2/union-by-rank
+    - https://www.coursera.org/learn/data-structures/lecture/Q9CVI/path-compression
+    - https://www.coursera.org/learn/data-structures/lecture/GQQLN/analysis-optional
+
+- [ ] **Priority Queue**
+    - Notes:
+        - visualized as a tree, but is usually linear in storage (array, linked list)
+    - https://en.wikipedia.org/wiki/Priority_queue
+    - https://www.youtube.com/watch?v=yIUFT6AKBGE&index=24&list=PL4BBB74C7D2A1049C
+
+## Graphs
+
+    This area is sparse (no pun intended), and I'll be filling it in once I get here.
+
+- Notes:
+    - 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
+    - If you get a chance, try to study up on fancier algorithms:
+        - Dijkstra's algorithm
+            - https://en.wikipedia.org/wiki/Dijkstra%27s_algorithm
+        - A*
+            - https://en.wikipedia.org/wiki/A*_search_algorithm
+    - When asked a question, look for a graph-based solution first, then move on if none.
+
+- Graphs:
+    - https://www.youtube.com/watch?v=ylWAB6CMYiY&list=PL4BBB74C7D2A1049C&index=27
+
+- Weighted graphs:
+    - https://www.youtube.com/watch?v=zFbq8vOZ_0k&list=PL4BBB74C7D2A1049C&index=28
+
+- Compute Strongly Connected Components
+    - [ ] https://www.coursera.org/learn/algorithms-on-graphs/home/week/5
+
+- Implement:
+
+    - [ ] Dijkstra's algorithm
+    - [ ] A*
+
+You'll get more graph practice in Skiena's book (see Books section below) and the interview books
+
+## Sorting
+
+    This area is sparse, and I'll be filling it in once I get here.
+
+- [ ] Notes:
+    - [ ] Implement & know best case/worst case, average complexity of each:
+        - no bubble sort - it's terrible - O(n^2)
+    - [ ] stability in sorting algorithms:
+        - http://stackoverflow.com/questions/1517793/stability-in-sorting-algorithms
+        - http://www.geeksforgeeks.org/stability-in-sorting-algorithms/
+    - [ ] Which algorithms can be used on linked lists?
+    - [ ] Which on arrays? Which on both?
+    - [ ] Is Quicksort stable?
+
+- [ ] Implement:
+    - [ ] Mergesort
+    - [ ] Quicksort
+    - [ ] Insertion Sort
+    - [ ] Selection Sort
+
+- For Curiosity:
+     - [ ] Radix Sort: https://www.youtube.com/watch?v=xhr26ia4k38
+
+## Even More Knowledge
+
+    This area is sparse, and I'll be filling it in once I get here.
+
+- [ ] Caches
+    - LRU cache
+
+- [ ] NP and NP Complete
+    - 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.
+
+- [ ] Recursion
+    -  when it is appropriate to use it
+
+- [ ] open-ended problems
+    - manipulate strings
+    - manipulate patterns
+
+- [ ] Combinatorics (n choose k)
+
+- [ ] Probability
+    - https://www.youtube.com/watch?v=sZkAAk9Wwa4
+    - https://www.youtube.com/watch?v=dNaJg-mLobQ
+
+- [ ] Dynamic Programming
+
+- [ ] Scheduling
+
+- [ ] Weighted random sampling
+
+- [ ] Implement system routines
+
+- [ ] Design patterns:
+    - description:
+        - https://www.lynda.com/Developer-Programming-Foundations-tutorials/Foundations-Programming-Design-Patterns/135365-2.html
+        - Patterns: https://www.youtube.com/playlist?list=PLF206E906175C7E07
+        - UML: https://www.youtube.com/playlist?list=PLGLfVvz_LVvQ5G-LdJ8RLqe-ndo7QITYc
+    - [ ] strategy
+    - [ ] singleton
+    - [ ] adapter
+    - [ ] prototype
+    - [ ] decorator
+    - [ ] visitor
+    - [ ] factory
+
+- [ ] **Operating Systems (25 videos):**
+    - https://www.youtube.com/watch?v=-KWd_eQYLwY&index=2&list=PL-XXv-cvA_iBDyz-ba4yDskqMDY6A1w_c
+    - 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 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++:
+        https://www.youtube.com/playlist?list=PL5jc9xFGsL8E12so1wlMS0r0hTQoJL74M
+        - stopped here: https://www.youtube.com/watch?v=_N0B5ua7oN8&list=PL5jc9xFGsL8E12so1wlMS0r0hTQoJL74M&index=4
+
+- [ ] **Data handling:**
+    - see scalability options below
+    - Distill large data sets to single values
+    - Transform one data set to another
+    - Handling obscenely large amounts of data
+
+- [ ] **System design**
+    - https://www.quora.com/How-do-I-prepare-to-answer-design-questions-in-a-technical-interview?redirected_qid=1500023
+    - features sets
+    - interfaces
+    - class hierarchies
+    - designing a system under certain constraints
+    - simplicity and robustness
+    - tradeoffs
+    - performance analysis and optimization
+
+- [ ] **Familiarize yourself with a unix-based code editor: emacs & vi(m)**
+    - suggested by Yegge
+    - vi(m):
+        - https://www.youtube.com/watch?v=5givLEMcINQ&index=1&list=PL13bz4SHGmRxlZVmWQ9DvXo1fEg4UdGkr
+        - set of 4:
+            - https://www.youtube.com/watch?v=SI8TeVMX8pk
+            - https://www.youtube.com/watch?v=F3OO7ZIOaJE
+            - https://www.youtube.com/watch?v=ZYEccA_nMaI
+            - https://www.youtube.com/watch?v=1lYD5gwgZIA
+    - emacs:
+        - https://www.youtube.com/watch?v=hbmV1bnQ-i0
+        - set of 3:
+            - https://www.youtube.com/watch?v=ujODL7MD04Q
+            - https://www.youtube.com/watch?v=XWpsRupJ4II
+            - https://www.youtube.com/watch?v=paSgzPso-yc
+        - https://www.youtube.com/watch?v=JWD1Fpdd4Pc
+
+- [ ] **Be able to use unix command line tools:**
+    - suggested by Yegge
+    - bash
+    - grep
+    - sed
+    - awk
+    - curl or wget
+
+- [ ] **Testing**
+    - how unit testing works
+    - what are mock onbjects
+    - what is integration testing
+    - what is dependency injection
+
+## Books
+
+#### Mentioned in Google Coaching:
+
+- [ ] The Algorithm Design Manual (Skiena)
+    - Book (can rent on kindle):
+        - http://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1849967202
+    - Answers:
+        - http://www.algorithm.cs.sunysb.edu/algowiki/index.php/The_Algorithms_Design_Manual_(Second_Edition)
+
+- [ ] Algorithms and Programming: Problems and Solutions:
+    http://www.amazon.com/Algorithms-Programming-Solutions-Alexander-Shen/dp/0817638474
+
+
+    Once you've understood everything in the daily plan, 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:**
+- [ ] Cracking the Coding Interview, 6th Edition:
+    - http://www.amazon.com/Cracking-Coding-Interview-6th-Programming/dp/0984782850/
+
+#### Additional books (not suggested by Google but I added):
+
+- [x] C Programming Language, Vol 2
+
+- [x] C++ Primer Plus, 6th Edition
+
+- [ ] Introduction to Algorithms
+    - https://www.amazon.com/Introduction-Algorithms-3rd-MIT-Press/dp/0262033844
+
+- [ ] Programming Pearls:
+    - http://www.amazon.com/Programming-Pearls-2nd-Jon-Bentley/dp/0201657880
+
+If you see people reference "The Google Resume", it was a book replaced by "Cracking the Coding Interview".
+
+## About Google
+
+- [ ] How Search Works:
+    - [ ] https://www.google.com/insidesearch/howsearchworks/thestory/
+    - [ ] https://www.youtube.com/watch?v=BNHR6IQJGZs
+    - [ ] https://www.google.com/insidesearch/howsearchworks/
+
+## Articles
+
+- https://www.topcoder.com/community/data-science/data-science-tutorials/the-importance-of-algorithms/
+- http://highscalability.com/blog/2016/4/4/how-to-remove-duplicates-in-a-large-dataset-reducing-memory.html
+- http://highscalability.com/blog/2016/3/23/what-does-etsys-architecture-look-like-today.html
+- http://highscalability.com/blog/2016/3/21/to-compress-or-not-to-compress-that-was-ubers-question.html
+- http://highscalability.com/blog/2016/3/3/asyncio-tarantool-queue-get-in-the-queue.html
+- http://highscalability.com/blog/2016/2/25/when-should-approximate-query-processing-be-used.html
+- http://highscalability.com/blog/2016/2/23/googles-transition-from-single-datacenter-to-failover-to-a-n.html
+- http://highscalability.com/blog/2016/2/15/egnyte-architecture-lessons-learned-in-building-and-scaling.html
+- http://highscalability.com/blog/2016/2/1/a-patreon-architecture-short.html
+- http://highscalability.com/blog/2016/1/27/tinder-how-does-one-of-the-largest-recommendation-engines-de.html
+- http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html
+- http://highscalability.com/blog/2016/1/13/live-video-streaming-at-facebook-scale.html
+- http://highscalability.com/blog/2016/1/11/a-beginners-guide-to-scaling-to-11-million-users-on-amazons.html
+- http://highscalability.com/blog/2015/12/16/how-does-the-use-of-docker-effect-latency.html
+- http://highscalability.com/blog/2015/12/14/does-amp-counter-an-existential-threat-to-google.html
+- http://highscalability.com/blog/2015/11/9/a-360-degree-view-of-the-entire-netflix-stack.html
+
+## Papers:
+
+Computing Weak Consistency in Polynomial Time
+    - http://dl.acm.org/ft_gateway.cfm?id=2767407&ftid=1607485&dwn=1&CFID=627637486&CFTOKEN=49290244
+
+How Developers Search for Code: A Case Study
+    - http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43835.pdf
+
+Borg, Omega, and Kubernetes
+    - http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/44843.pdf
+
+Continuous Pipelines at Google
+    - http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43790.pdf
+
+AddressSanitizer: A Fast Address Sanity Checker
+    - http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/37752.pdf
+
+## 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.
+
+- https://courses.csail.mit.edu/iap/interview/materials.php
+
+The Best:
+- LeetCode: https://leetcode.com/
+- Project Euler: https://projecteuler.net/index.php?section=problems
+- TopCoder: https://www.topcoder.com/
+
+More:
+- HackerRank: https://www.hackerrank.com/
+- Codility: https://codility.com/programmers/
+- InterviewCake: https://www.interviewcake.com/
+- InterviewBit: https://www.interviewbit.com/invite/icjf
+
+
+## Once you're closer to the interview:
+
+- [ ] Cracking The Coding Interview Set 2:
+    - https://www.youtube.com/watch?v=4NIb9l3imAo
+    - https://www.youtube.com/watch?v=Eg5-tdAwclo
+    - https://www.youtube.com/watch?v=1fqxMuPmGak
+
+## Your Resume
+
+- http://steve-yegge.blogspot.co.uk/2007_09_01_archive.html
+
+
+## Be thinking of for when the interview comes:
+
+- Think of about 20 interview questions you'll get, along the lines of the items below:
+- have 2-3 answers 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 Google 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]?
+
+### Have questions for the interviewer.
+
+Some of mine (I already may know answer to but want their opinion or team perspective):
+
+- How large is your team?
+- What is your dev cycle look like? Do you do waterfall/sprints/agile?
+- Are rushes to deadlines common? Or is there flexibility?
+- How are decisions made in your team?
+- How many meetings do you have per week?
+- Do you feel your work environment helps you concentrate?
+- What are you working on?
+- What do you like about it?
+- What is the work life like?
+
+---
+
+## Additional Resources
+
+    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.
+
+- [ ] Vector calculus
+
+- [ ] Computer Security:
+    - MIT (23 videos): https://www.youtube.com/playlist?list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh
+
+- [ ] Information theory:
+    - Markov processes:
+        - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/waxgx/core-markov-text-generation
+        - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/gZhiC/core-implementing-markov-text-generation
+    - https://www.khanacademy.org/computing/computer-science/informationtheory/moderninfotheory/v/symbol-rate-information-theory
+    - includes Markov chain
+
+- [ ] Bloom Filter
+    - https://www.youtube.com/watch?v=-SuTGoFYjZs
+    - http://blog.michaelschmatz.com/2016/04/11/how-to-write-a-bloom-filter-cpp/
+
+- [ ] Fast Fourier Transform
+    - http://jakevdp.github.io/blog/2013/08/28/understanding-the-fft/
+
+- [ ] Machine Learning:
+    - great course: https://www.coursera.org/learn/machine-learning
+    - http://www.analyticsvidhya.com/blog/2016/04/neural-networks-python-theano/
+    - http://www.dataschool.io/
+
+- [ ] Parallel Programming:
+    - https://www.coursera.org/learn/parprog1/home/week/1
+
+- [ ] String search algorithms:
+    Knuth-Morris-Pratt (KMP):
+        - https://en.wikipedia.org/wiki/Knuth%E2%80%93Morris%E2%80%93Pratt_algorithm
+        - https://www.youtube.com/watch?v=2ogqPWJSftE
+    Boyer–Moore string search algorithm
+        - https://en.wikipedia.org/wiki/Boyer%E2%80%93Moore_string_search_algorithm
+        - https://www.youtube.com/watch?v=xYBM0_dChRE
+
+## Videos
+
+Sit back and enjoy. "netflix and skill" :P
+
+- [ ] Scalability:
+    - https://www.youtube.com/watch?v=9nWyWwY2Onc
+    - https://www.youtube.com/watch?v=H4vMcD7zKM0
+
+- [ ] CSE373 - Analysis of Algorithms (25 videos):
+    - Skiena lectures from Algorithm Design Manual
+    - https://www.youtube.com/watch?v=ZFjhkohHdAA&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=1
+
+- [ ] UC Berkeley 61B
+    - https://www.youtube.com/playlist?list=PL4BBB74C7D2A1049C
+
+- [ ] MIT 6.042: Math for CS (25 videos):
+    - https://www.youtube.com/watch?v=L3LMbpZIKhQ&list=PLB7540DEDD482705B
+
+- [ ] MIT 6.006: Intro to Algorithms (47 videos):
+    - https://www.youtube.com/watch?v=HtSuA80QTyo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&nohtml5=False
+
+- [ ] MIT 6.033: Computer System Engineering (22 videos):
+    - https://www.youtube.com/watch?v=zm2VP0kHl1M&list=PL6535748F59DCA484
+
+- [ ] MIT 6.046: Design and Analysis of Algorithms (34 videos):
+    - https://www.youtube.com/watch?v=2P-yW7LQr08&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp
+
+- [ ] MIT 6.858 Computer Systems Security, Fall 2014 ():
+    - https://www.youtube.com/watch?v=GqmQg-cszw4&index=1&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh
+
+- [ ] MIT 6.851: Advanced Data Structures (22 videos):
+    - https://www.youtube.com/watch?v=T0yzrZL1py0&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf&index=1
+
+- [ ] Stanford: Programming Paradigms (17 videos)
+    - Course on C and C++
+    - https://www.youtube.com/watch?v=jTSvthW34GU&list=PLC0B8B318B7394B6F&nohtml5=False
+
+- [ ] MIT 6.050J Information and Entropy, Spring 2008 ()
+    - https://www.youtube.com/watch?v=phxsQrZQupo&list=PL_2Bwul6T-A7OldmhGODImZL8KEVE38X7
+
+- [ ] Introduction to Cryptography:
+    - https://www.youtube.com/watch?v=2aHkqB2-46k&feature=youtu.be
+
+## Maybe
+
+http://www.gainlo.co/ - Mock interviewers from big companies
+
+## Code References
+
+For review questions in C book:
+    https://github.com/lekkas/c-algorithms
+
+## Once You've Got The Job
+
+This is mainly for me.
+
+- [ ] Books:
+    - [ ] Clean Code
+    - [ ] Code Complete
+    - [ ] How to Prove It: A Structured Approach, 2nd Edition
+    - [ ] Unix Power Tools, Third Edition
+
+- [x] C++ Seasoning:
+    - https://www.youtube.com/watch?v=qH6sSOr-yk8
+
+- [x] Better Code: Data Structures:
+    - https://www.youtube.com/watch?v=sWgDk-o-6ZE
+
+- [ ] C++ Talks at CPPCon:
+    - https://www.youtube.com/watch?v=hEx5DNLWGgA&index=2&list=PLHTh1InhhwT75gykhs7pqcR_uSiG601oh
+
+- [ ] MIT CMS.611J Creating Video Games, Fall 2014
+    - https://www.youtube.com/watch?v=pfDfriSjFbY&list=PLUl4u3cNGP61V4W6yRm1Am5zI94m33dXk
+
+- [ ] Compilers:
+    - https://class.coursera.org/compilers-004/lecture
+
+- [ ] Computer and processor architecture:
+    - https://class.coursera.org/comparch-003/lecture
+
+- [ ] Long series of C++ videos:
+    - https://www.youtube.com/playlist?list=PLfVsf4Bjg79Cu5MYkyJ-u4SyQmMhFeC1C
+
+## Done
+
+You're never really done. Keep learning.