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Google Interview University

Translations:

What is it?

This is my multi-month study plan for going from web developer (self-taught, no CS degree) to Google software engineer.

Coding at the whiteboard - from HBO's Silicon Valley

This long list has been extracted and expanded from Google's coaching notes, so these are the things you need to know. There are extra items I added at the bottom that may come up in the interview or be helpful in solving a problem. Many items are from Steve Yegge's "Get that job at Google" and are reflected sometimes word-for-word in Google's coaching notes.

I've pared down what you need to know from what Yegge recommends. I've altered Yegge's requirements from information received from my contact at Google. This is meant for new software engineers or those switching from software/web development to software engineering (where computer science knowledge is required). If you have many years of experience and are claiming many years of software engineering experience, expect a harder interview. Read more here.

If you have many years of software/web development experience, note that Google views software engineering as different from software/web development and they require computer science knowledge.

If you want to be a reliability engineer or systems engineer, study more from the optional list (networking, security).

Table of Contents

---------------- Everything below this point is optional ----------------

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 project, I didn't know a stack from a heap, didn't know Big-O anything, anything about trees, or how to traverse a graph. If I had to code a sorting algorithm, I can tell ya it wouldn't have been very good. Every data structure I've ever used was built into the language, and I didn't know how they worked under the hood at all. I've never had to manage memory unless a process I was running would give an "out of memory" error, and then I'd have to find a workaround. I've used a few multidimensional arrays in my life and thousands of associative arrays, but I've never created data structures from scratch.

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 progress.

Create a new branch so you can check items like this, just put an x in the brackets: [x]

Fork a branch and follow the commands below

git checkout -b progress

git remote add jwasham https://github.com/jwasham/google-interview-university

git fetch --all

Mark all boxes with X after you completed your changes

git add .

git commit -m "Marked x"

git rebase jwasham/master

git push --force

More about Github-flavored markdown

Get in a Googley Mood

Print out a "future Googler" sign (or two) and keep your eyes on the prize.

future Googler sign

Did I Get the Job?

I'm in the queue right now. Hope to interview soon.

Thanks for the referral, JP.

Follow Along with Me

My story: Why I Studied Full-Time for 8 Months for a Google Interview

I'm on the journey, too. Follow along:

John Washam - Google Interview University

Don't feel you aren't smart enough

About Google

About Video Resources

Some videos are available only by enrolling in a Coursera, EdX, or Lynda.com class. These are called MOOCs. Sometimes the classes are not in session so you have to wait a couple of months, so you have no access. Lynda.com courses are not free.

I'd appreciate your help to add free and always-available public sources, such as YouTube videos to accompany the online course videos.
I like using university lectures.

Interview Process & General Interview Prep

Pick One Language for the Interview

I wrote this short article about it: Important: Pick One Language for the Google Interview

You can use a language you are comfortable in to do the coding part of the interview, but for Google, these are solid choices:

You could also use these, but read around first. There may be caveats:

You need to be very comfortable in the language and be knowledgeable.

Read more about choices:

See language resources here

You'll see some C, C++, and Python learning included below, because I'm learning. There are a few books involved, see the bottom.

Book List

This is a shorter list than what I used. This is abbreviated to save you time.

Interview Prep

If you have tons of extra time:

Computer Architecture

If short on time:

If you have more time (I want this book):

Language Specific

You need to choose a language for the interview (see above). Here are my recommendations by language. I don't have resources for all languages. I welcome additions.

If you read though one of these, you should have all the data structures and algorithms knowledge you'll need to start doing coding problems. You can skip all the video lectures in this project, unless you'd like a review.

Additional language-specific resources here.

C++

I haven't read these two, but they are highly rated and written by Sedgewick. He's awesome.

If you have a better recommendation for C++, please let me know. Looking for a comprehensive resource.

Java

OR:

Python

Optional Books

Some people recommend these, but I think it's going overboard, unless you have many years of software engineering experience and expect a much harder interview:

Before you Get Started

This list grew over many months, and yes, it kind of got out of hand.

Here are some mistakes I made so you'll have a better experience.

1. You Won't Remember it All

I watched hours of videos and took copious notes, and months later there was much I didn't remember. I spent 3 days going through my notes and making flashcards so I could review.

Read please so you won't make my mistakes:

Retaining Computer Science Knowledge

2. Use Flashcards

To solve the problem, I made a little flashcards site where I could add flashcards of 2 types: general and code. Each card has different formatting.

I made a mobile-first website so I could review on my phone and tablet, wherever I am.

Make your own for free:

Keep in mind I went overboard and have cards covering everything from assembly language and Python trivia to machine learning and statistics. It's way too much for what's required by Google.

Note on flashcards: The first time you recognize you know the answer, don't mark it as known. You have to see the same card and answer it several times correctly before you really know it. Repetition will put that knowledge deeper in your brain.

An alternative to using my flashcard site is Anki, which has been recommended to me numerous times. It uses a repetition system to help you remember. It's user-friendly, available on all platforms and has a cloud sync system. It costs $25 on iOS but is free on other platforms.

My flashcard database in Anki format: https://ankiweb.net/shared/info/25173560 (thanks @xiewenya)

3. Review, review, review

I keep a set of cheat sheets on ASCII, OSI stack, Big-O notations, and more. I study them when I have some spare time.

Take a break from programming problems for a half hour and go through your flashcards.

4. Focus

There are a lot of distractions that can take up valuable time. Focus and concentration are hard.

What you won't see covered

This big list all started as a personal to-do list made from Google interview coaching notes. These are prevalent technologies but were not mentioned in those notes:

The Daily Plan

Some subjects take one day, and some will take multiple days. Some are just learning with nothing to implement.

Each day I take one subject from the list below, watch videos about that subject, and write an implementation in:

You don't need all these. You need only one language for the interview.

Why code in all of these?

I may not have time to do all of these for every subject, but I'll try.

You can see my code here:

You don't need to memorize the guts of every algorithm.

Write code on a whiteboard or paper, not a computer. Test with some sample inputs. Then test it out on a computer.

Prerequisite Knowledge

Algorithmic complexity / Big-O / Asymptotic analysis

Data Structures

More Knowledge

Trees

Sorting

If you need more detail on this subject, see "Sorting" section in Additional Detail on Some Subjects

Graphs

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

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

Even More Knowledge

System Design, Scalability, Data Handling

Final Review

This section will have shorter videos that you can watch pretty quickly to review most of the important concepts.
It's nice if you want a refresher often.

Coding Question Practice

Now that you know all the computer science topics above, it's time to practice answering coding problems.

Coding question practice is not about memorizing answers to programming problems.

Why you need to practice doing programming problems:

There is a great intro for methodical, communicative problem solving in an interview. You'll get this from the programming interview books, too, but I found this outstanding: Algorithm design canvas

My Process for Coding Interview (Book) Exercises

No whiteboard at home? That makes sense. I'm a weirdo and have a big whiteboard. Instead of a whiteboard, pick up a large drawing pad from an art store. You can sit on the couch and practice. This is my "sofa whiteboard". I added the pen in the photo for scale. If you use a pen, you'll wish you could erase. Gets messy quick.

my sofa whiteboard

Supplemental:

Read and Do Programming Problems (in this order):

See Book List above

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.

Challenge sites:

Maybe:

Once you're closer to the interview

Your Resume

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 2-3 answers for each. Have a story, not just data, about something you accomplished.

Have questions for the interviewer

Some of mine (I already may know answer to but want their opinion or team perspective):

Once You've Got The Job

Congratulations!

Keep learning.

You're never really done.

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Everything below this point is optional. These are my recommendations, not Google's.
By studying these, you'll get greater exposure to more CS concepts, and will be better prepared for
any software engineering job. You'll be a much more well-rounded software engineer.

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Additional Books

Additional Learning

--

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?

Video Series

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

Computer Science Courses