DSA & Coding Interviews Mastery Path¶

Mastery Path

BOOTCAMP

VINOD BHANUJA

This course teaches data structures and algorithms the way you will actually use them: to solve an unfamiliar problem on a whiteboard or in a shared editor, under time pressure, while explaining your thinking to another engineer. It starts with Big-O and plain arrays and ends with a complete mock interview transcript you can grade yourself against.

All solutions are written in Python 3. Python keeps the code short enough that the idea stays visible, and its standard library (collections, heapq, bisect) covers most interview needs. Nothing here depends on Python, though: the patterns, invariants and complexity arguments carry over directly to Java, C++, Go, JavaScript or whatever language you interview in. Where Python hides a cost (slicing copies, list.pop(0) is linear, recursion depth is limited), the lessons point it out.

Memorizing hundreds of problems does not scale. What does scale is recognizing a small set of patterns — two pointers, sliding window, BFS, backtracking, dynamic programming, monotonic stacks — and knowing why each one works. So most lessons follow the same problem-solving arc: introduce the pattern, work a problem from brute force to a clean solution, analyze time and space, walk through the edge cases, and finish with variations. Every lesson also has a How It Actually Works section that explains the mechanism behind the complexity: how a hash table resolves collisions, why appending to a dynamic array is amortized O(1), how a heap restores order in O(log n), why union-find with path compression is nearly constant time.

Every main solution on this site includes assert-based test cases, including edge cases, so you can paste it into a file and run it with python3 file.py. If the file prints nothing, all tests passed.

How the program is organized¶

Level	Focus	Modules
Level 1 · Entry	Complexity, arrays, hashing, two pointers, sliding window, stacks, linked lists, recursion, binary search	9 topics + 1 timed practice set
Level 2 · Intermediate	Trees, BSTs, heaps, graph traversal, backtracking, first DP, prefix sums, greedy, tries	9 topics + 1 timed practice set
Level 3 · Advanced	Advanced DP, shortest paths, topological sort, union-find, monotonic structures, bits, range-query trees, string algorithms, MSTs	9 topics + 1 hard problem set
Level 4 · Master	Communication framework, behavioral prep, mock walkthroughs, online assessments, live debugging, offers, study plans	9 topics + 1 capstone (full mock interview)

How to use this site¶

Levels 1 and 2 cover what most coding interviews draw on. Level 3 covers topics that come up less often but separate strong candidates on harder rounds. Level 4 is about the interview itself — you can read it in parallel with the others.
Try every worked problem yourself before reading the solution. Give it 15–20 minutes. Getting stuck and then seeing the key idea is how the pattern sticks.
Say your approach out loud (or write it as comments) before coding. Interviewers grade the reasoning, not just the final code.
Do the Exercise at the end of each lesson. The practice sets at the end of each level are timed on purpose — treat them like the real thing.
If your Python is rusty, the Python Mastery Path covers the language itself.

Start here → Level 1 · Entry

🎥 Prefer video? Watch the Mastery Path video series on YouTube — Shorts and full walkthroughs of lessons across the series.