₹0 for students · Certificate · Intermediate

Coding Interview Practice

4 mini courses, 16 lessons: the interview method and the 12 patterns behind most coding questions

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16 lessons · ~3 hours · 30-question final exam · pass mark 70%

About the course

What you’ll learn

Prepare for online assessments and technical rounds at product companies, service companies and startups. Learn a repeatable method for any problem, then the patterns that solve most questions: two pointers, sliding windows, hashing, binary search, stacks, trees, recursion and backtracking, graphs, dynamic programming, greedy and heaps. Every lesson has a real problem to solve in the browser. Pass every lesson quiz and the final exam to earn a verifiable certificate.

Problem solvingData structuresAlgorithmsCoding interviewsPython

Part of the career track: Computer Science Foundations

How the certificate works

  1. Read each lesson’s study guide, then the full lesson and any notebooks or exercises.
  2. Pass every lesson quiz with 70% or more.
  3. Pass the final exam: 30 questions in 45 minutes.
  4. Get a certificate with a public verification link, and add it to LinkedIn.

Syllabus

16 lessons in 4 mini courses

Each mini course takes about an hour. Already know one? Test out in the app and skip it.

1. The interview method

Approach any coding question with a clear method and explain your thinking.

1
How Tech Hiring Works
10 min · Typical funnel: online assessment → technical rounds → manager/HR round.
2
A Method for Any Problem
12 min · Understand: restate, ask about sizes and edge cases.
3
Talking About Complexity
10 min · Say time and space complexity for every solution.
4
Thinking Aloud and Testing
10 min · Think aloud: what you're trying and why.

2. Arrays and strings

Solve array and string problems with two pointers, windows, hashing and binary search.

5
Two Pointers
12 min · Two pointers replace nested loops with one pass.
6
Sliding Window
12 min · Sliding windows handle contiguous subarrays and substrings.
7
Hash Maps and Prefix Sums
12 min · "Store what you've seen" in a hash map turns O(n²) into O(n).
8
Binary Search Beyond Sorted Arrays
12 min · Binary search halves the range: O(log n).

3. Stacks, trees and recursion

Use stacks, linked-list tricks, tree traversals and backtracking.

9
Stack Patterns
10 min · Stacks handle nesting and most-recent-first.
10
Linked List Tricks
10 min · Reverse with prev, current and next pointers.
11
Tree Problems: DFS and BFS
12 min · Recursion: handle None, then combine left and right answers.
12
Recursion and Backtracking
12 min · Backtracking: choose, explore, unchoose.

4. Graphs, DP, greedy and heaps

Solve graph, dynamic programming, greedy and top-k problems.

13
Graph Problems
12 min · Grids, prerequisites and word ladders are graphs in disguise.
14
Dynamic Programming
14 min · DP stores answers to overlapping subproblems.
15
Greedy Choices and Intervals
10 min · Greedy takes the best local choice and never revisits it.
16
Heaps and Top-K Problems
10 min · Heaps: min or max in O(1), push/pop in O(log n).

Written by Vikosha. Lessons, questions and exercises are original. Licence: Original Vikosha course..