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I originally created this as a short to-do list of study topics for becoming a software engineer, but it grew to the large list you see today. After going through this study plan, I got hired as a Software Development Engineer at Amazon! You probably won't have to study as much as I did. Anyway, everything you need is here.
I studied about 8-12 hours a day, for several months. This is my story: Why I studied full-time for 8 months for a Google interview
Please Note: You won't need to study as much as I did. I wasted a lot of time on things I didn't need to know. More info about that below. I'll help you get there without wasting your precious time.
The items listed here will prepare you well for a technical interview at just about any software company, including the giants: Amazon, Facebook, Google, and Microsoft.
Best of luck to you!
This is my multi-month study plan for becoming a software engineer for a large company.
Required:
Note this is a study plan for software engineering, not web development. Large software companies like Google, Amazon, Facebook and Microsoft view software engineering as different from web development. For example, Amazon has Frontend Engineers (FEE) and Software Development Engineers (SDE). These are 2 separate roles and the interviews for them will not be the same, as each has its own competencies. These companies require computer science knowledge for software development/engineering roles.
---------------- Everything below this point is optional ----------------
If you want to work as a software engineer for a large company, these are the things you have to know.
If you missed out on getting a degree in computer science, like I did, this will catch you up and save four years of your life.
When I started this project, I didn't know a stack from a heap, didn't know Big-O anything, or anything about trees, or how to traverse a graph. If I had to code a sorting algorithm, I can tell ya it would have been terrible. Every data structure I had ever used was built into the language, and I didn't know how they worked under the hood at all. I 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 used a few multidimensional arrays in my life and thousands of associative arrays, but I never created data structures from scratch.
It's a long plan. It may take you months. If you are familiar with a lot of this already it will take you a lot less time.
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 track 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
Fork the GitHub repo https://github.com/jwasham/coding-interview-university by clicking on the Fork button.
Clone to your local repo:
git clone git@github.com:<your_github_username>/coding-interview-university.git
git checkout -b progress
git remote add jwasham https://github.com/jwasham/coding-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/main
git push --set-upstream origin progress
git push --force
More about GitHub-flavored markdown
Some videos are available only by enrolling in a Coursera or EdX 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.
It would be great to replace the online course resources with free and always-available public sources, such as YouTube videos (preferably university lectures), so that you people can study these anytime, not just when a specific online course is in session.
You'll need to choose a programming language for the coding interviews you do, but you'll also need to find a language that you can use to study computer science concepts.
Preferably the language would be the same, so that you only need to be proficient in one.
When I did the study plan, I used 2 languages for most of it: C and Python
This is my preference. You do what you like, of course.
You may not need it, but here are some sites for learning a new language:
You can use a language you are comfortable in to do the coding part of the interview, but for large companies, these are solid choices:
You could also use these, but read around first. There may be caveats:
Here is an article I wrote about choosing a language for the interview: Pick One Language for the Coding Interview. This is the original article my post was based on: http://blog.codingforinterviews.com/best-programming-language-jobs/
You need to be very comfortable in the language and be knowledgeable.
Read more about choices:
See language-specific resources here
This book will form your foundation for computer science.
Just choose one, in a language that you will be comfortable with. You'll be doing a lot of reading and coding.
Your choice:
Your choice:
You don't need to buy a bunch of these. Honestly "Cracking the Coding Interview" is probably enough, but I bought more to give myself more practice. But I always do too much.
I bought both of these. They gave me plenty of practice.
Choose one:
This list grew over many months, and yes, it got out of hand.
Here are some mistakes I made so you'll have a better experience. And you'll save months of time.
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. I didn't need all of that knowledge.
Please, read so you won't make my mistakes:
Retaining Computer Science Knowledge.
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 or tablet, wherever I am.
Make your own for free:
I DON'T RECOMMEND using my flashcards. There are too many and many of them are trivia that you don't need.
But if you don't want to listen to me, here you go:
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.
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).
Some students have mentioned formatting issues with white space that can be fixed by doing the following: open deck, edit card, click cards, select the "styling" radio button, add the member "white-space: pre;" to the card class.
THIS IS VERY IMPORTANT.
Start doing coding interview questions while you're learning data structures and algorithms.
You need to apply what you're learning to solving problems, or you'll forget. I made this mistake.
Once you've learned a topic, and feel somewhat comfortable with it, for example, linked lists:
Keep doing problems while you're learning all this stuff, not after.
You're not being hired for knowledge, but how you apply the knowledge.
There are many resources for this, listed below. Keep going.
There are a lot of distractions that can take up valuable time. Focus and concentration are hard. Turn on some music without lyrics and you'll be able to focus pretty well.
These are prevalent technologies but not part of this study plan:
This course goes over a lot of subjects. Each will probably take you a few days, or maybe even a week or more. It depends on your schedule.
Each day, take the next subject in the list, watch some videos about that subject, and then write an implementation of that data structure or algorithm in the language you chose for this course.
You can see my code here:
You don't need to memorize every algorithm. You just need to be able to understand it enough to be able to write your own implementation.
Why is this here? I'm not ready to interview.
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
Write code on a whiteboard or paper, not a computer. Test with some sample inputs. Then type it and test it out on a computer.
If you don't have a whiteboard at home, 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 just for scale. If you use a pen, you'll wish you could erase. Gets messy quick. I use a pencil and eraser.
Coding question practice is not about memorizing answers to programming problems.
Don't forget your key coding interview books here.
Solving Problems:
Coding Interview Question Videos:
Challenge sites:
Alright, enough talk, let's learn!
But don't forget to do coding problems from above while you learn!
Well, that's about enough of that.
When you go through "Cracking the Coding Interview", there is a chapter on this, and at the end there is a quiz to see if you can identify the runtime complexity of different algorithms. It's a super review and test.
Videos:
Online Courses:
Implement with array using linear probing
Notes:
For heapsort, see Heap data structure above. Heap sort is great, but not stable
UC Berkeley:
Merge sort code:
Quick sort code:
Implement:
Not required, but I recommended them:
As a summary, here is a visual representation of 15 sorting algorithms. If you need more detail on this subject, see "Sorting" section in Additional Detail on Some Subjects
Graphs can be used to represent many problems in computer science, so this section is long, like trees and sorting were.
Notes:
MIT(videos):
Skiena Lectures - great intro:
Graphs (review and more):
Full Coursera Course:
I'll implement:
If you need more detail on this subject, see "String Matching" section in Additional Detail on Some Subjects.
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.
Mock Interviews:
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:
Some of mine (I already may know the answers, but want their opinion or team perspective):
Congratulations!
Keep learning.
You're never really done.
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Everything below this point is optional. It is NOT needed for an entry-level interview.
However, 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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These are here so you can dive into a topic you find interesting.
You can expect system design questions if you have 4+ years of experience.
I added them to help you become a well-rounded software engineer, and to be aware of certain
technologies and algorithms, so you'll have a bigger toolbox.
Know at least one type of balanced binary tree (and know how it's implemented):
"Among balanced search trees, AVL and 2/3 trees are now passé, and red-black trees seem to be more popular. A particularly interesting self-organizing data structure is the splay tree, which uses rotations to move any accessed key to the root." - Skiena
Of these, I chose to implement a splay tree. From what I've read, you won't implement a balanced search tree in your interview. But I wanted exposure to coding one up and let's face it, splay trees are the bee's knees. I did read a lot of red-black tree code
I want to learn more about B-Tree since it's used so widely with very large data sets
AVL trees
Splay trees
Red/black trees
2-3 search trees
2-3-4 Trees (aka 2-4 trees)
N-ary (K-ary, M-ary) trees
B-Trees
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
Union-Find
More Dynamic Programming (videos)
Advanced Graph Processing (videos)
MIT Probability (mathy, and go slowly, which is good for mathy things) (videos):
String Matching
Sorting
Sit back and enjoy.
List of individual Dynamic Programming problems (each is short)
Excellent - MIT Calculus Revisited: Single Variable Calculus
CSE373 - Analysis of Algorithms (25 videos)
UC Berkeley CS 152: Computer Architecture and Engineering (20 videos)
Carnegie Mellon - Computer Architecture Lectures (39 videos)
MIT 6.042J: Mathematics for Computer Science, Fall 2010 (25 videos)
MIT 6.050J: Information and Entropy, Spring 2008 (19 videos)
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