Skip to content

abondyuk/google-interview-university

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Google Interview University

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.


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 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 progress.

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

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 haven't applied yet.

I still have a few days in the learning phase (finishing up this crazy list), and starting next week all I'll be doing is programming questions all day long. That will continue for a few weeks, and then I'll apply through a referral I've been holding onto since February (yes, February).

Thanks for the referral, JP.

Follow Along with Me

I'm on the journey, too. Follow along on my blog at GoogleyAsHeck.com

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. It is free to do so, but sometimes the classes are not in session so you have to wait a couple of months, so you have no access.

I'd appreciate your help converting the MOOC video links to public sources to replace the online course videos over time. 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:

  • C++
  • Java
  • Python

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

  • JavaScript
  • Ruby

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.

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 (see below).

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, whereever I am.

Make your own for free:

  • Flashcards site repo
  • My flash cards database: 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.

3. Review, review, review

I keep a set of cheatsheets 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 is 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:

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

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: 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 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

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


Final Review

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

General:

  • Series of 2-3 minutes short subject videos (23 videos)
  • Series of 2-5 minutes short subject videos - Michael Sambol (18 videos):

Sorts:

Coding Question Practice

Books

Mentioned in Google Coaching

Read and do exercises:

  • The Algorithm Design Manual (Skiena)

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

Read first:

Read second (recommended by many, but not in Google coaching docs):

Additional books

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

If you have time

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.

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 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?

Once You've Got The Job

Congratulations!

Keep learning.

You're never really done.


*****************************************************************************************************
*****************************************************************************************************

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.

*****************************************************************************************************
*****************************************************************************************************

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

About

A complete daily plan for studying to become a Google software engineer.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published