When I was preparing for my FAANG interviews, I wish someone had sat me down and said: "Here is exactly what to do, in what order, and what not to waste your time on." Nobody did that for me, so I am doing it for you.
This is the roadmap I built for myself over 6-8 months of intense preparation. It is not a textbook outline or a generic checklist you find on some random blog. It is the actual path I walked -- the resources I used, the mistakes I made, and the topics that actually showed up in my interviews. If you follow this honestly, you will be ready.
One thing before we start: consistency beats intensity. I tried the "grind 12 hours a day for 2 weeks" approach and burned out completely. What actually worked was 2-3 focused hours every single day, no exceptions. Even on the days when I wanted to throw my laptop out the window.
The Study Roadmap
I have laid this out in the exact order I would follow if I had to do it all over again. Don't skip ahead. Each milestone builds on the last, and the order matters more than you think.
01
Time and Space Complexity
Get a basic understanding of what it means, how complexities are calculated, and then let your intuition grow as you solve more problems. Don't make the mistake I made of trying to "complete" a complexity theory course before writing any code -- you will learn this best by doing.
The single most important thing I learned in my entire prep journey: if you can think recursively, you can solve almost anything. This is the foundation everything else is built on -- backtracking, trees, graphs, DP, all of it starts with recursion.
Work through these categories in order. I have listed the completion percentages I aimed for -- and trust me, the ones marked 100% are worth doing every single problem:
String (Complete - 100%)
Array (Complete - 100%)
Backtracking (Complete - 100%)
Binary Tree (Complete - 60%)
Binary Search Tree (Complete - 60%)
Dynamic Programming (Complete - 100%)
Matrix (Complete - 100%)
Graphs (Complete - 100%)
3 monthsCore
A word about the 3 months above -- yes, it is a long time. I spent roughly 3 months on this alone and it was worth every single hour. There were days I stared at a recursion problem for 2 hours and got nowhere. That frustration is normal. It means your brain is rewiring itself to think differently. Stick with it.
03
Dynamic Programming Deep-Dive
DP deserves its own dedicated milestone because it is where most people hit a wall. I certainly did. Before diving into DP problems, read these resources to build your mental model -- understanding why DP works matters more than memorizing patterns.
Then come back to the DP problems on Techiedelight. Start there because those problems are gentler, and build up to the harder ones.
You might think "I already know sorting" -- and maybe you do. But can you implement merge sort from memory without looking anything up? Can you explain quicksort's partition step to someone with zero CS background? That is the bar. If you cannot, spend the time here.
Binary Search -- know it cold. Not just the textbook version, but all its variants (lower bound, upper bound, search in rotated array). It shows up everywhere.
Fundamentals
05
Binary Search Problems
Binary search looks simple on paper, but the number of ways interviewers twist it will surprise you. I underestimated this topic early on and it cost me in a couple of interviews. Spend real time here building intuition for where binary search applies in non-obvious situations.
At this point in my prep, I started to feel something shift. Problems that seemed impossible a month ago began to feel approachable. If you are in the thick of it right now and nothing is clicking -- keep going. The "aha" moment comes suddenly, and it comes for everyone who puts in the hours.
06
Heap Data Structure
Heaps are one of those topics that seem small but punch way above their weight in interviews. "Find the K-th largest element" is practically a rite of passage in tech interviews. Understand heaps deeply -- not just how to use a library's priority queue, but how the data structure works internally.
Once you see the sliding window pattern, you start seeing it everywhere. This is one of those techniques that immediately makes you faster in interviews because so many array and string problems are really just sliding window problems in disguise.
I am not going to sugarcoat it -- graphs came up in every single interview I had. Not always as an explicit "graph problem," but as something that was secretly a graph underneath (dependency resolution, network reachability, shortest path in a grid). If you only have time to go deep on one advanced topic, make it graphs.
09
Coding Platforms -- The Grind
Now it is time to put it all together. Solve medium and hard level questions on LeetCode for about a month. Don't just solve them -- simulate real interview conditions. Set a 45-minute timer, no looking at hints, and write clean code. That is how it will feel on the day.
Still hungry for more? These are some of my favorite challenge problems:
These are not strictly required, but knowing them gives you an edge -- especially for senior roles or companies that love data structure design questions. I learned Tries specifically because a friend told me it came up in his Google interview. He was right to warn me.
I watched a lot of YouTube during my prep. Most of it was useless. These four channels were the exception -- their explanations are clear, visual, and interview-focused:
Irfan Baqui -- complete all problems on this channel, seriously
Abdul Bari -- the best at making complex algorithms feel simple
Byte By Byte -- complete all problems on this channel too
Company Coding Problems Corner - Must Do
Here is something I wish I had known earlier: companies tend to recycle question patterns. Not the exact questions, but the types of problems. Practicing company-tagged problems gives you a real sense of what to expect.
At minimum, work through problems tagged for: Google, Facebook, Amazon, Microsoft, DE Shaw, Directi, Oracle, Adobe, Samsung, Ola, and Walmart Labs.
I am giving Google its own section because preparing for Google taught me more than preparing for any other company. Try finding solutions on YouTube first (preferably on the channels I recommended above -- they have genuinely excellent explanations), and then search elsewhere.
Here is a tip that made a huge difference for me: when you find a Google problem, don't just solve it. Look at the related problems that come up in the search results. Follow that rabbit hole. You will discover patterns and connections that make you a fundamentally better problem solver. Trust me, invest your time in this particular section.
I will be honest -- I did not read many books cover to cover. But this one is worth having on your desk:
"Cracking the Coding Interview" -- use it for the basics and the problem-solving framework, not as your primary problem source. The real learning happens on platforms like LeetCode and Techiedelight.
End Note
I never expected switching jobs to be this difficult. If you are in the middle of it right now and feeling frustrated, exhausted, or questioning whether you are cut out for this -- I have been exactly where you are. Things don't always go as planned. Sometimes you prepare for months and still don't clear an interview because the interviewer had a bad day, or the question was something you had never seen, or a hundred other things outside your control.
There is a role of chance and luck in this process, and accepting that is not weakness -- it is wisdom. What you can control is your preparation, your consistency, and your attitude. Focus on those.
A Sanskrit verse from the Bhagavad Gita keeps me grounded during those difficult moments. I keep coming back to it whenever rejection stings:
कर्मण्येवाधिकारस्ते मा फलेषु कदाचन। मा कर्मफलहेतुर्भूर्मा ते सङ्गोऽस्त्वकर्मणि॥
"You have the right to work only, but never to its fruits. Let not the fruits of action be your motive, nor let your attachment be to inaction."
-- Bhagavad Gita, Chapter 2, Verse 47
Do your work with full dedication, and let go of the anxiety about results. That is the only way to stay sane through this process -- and frankly, it is good advice for the rest of life too.