Data Structures and Algorithms Roadmap 2026
6 phases · 16 weeks · build one project in every phase.
Step-by-step plan
- Language basics in Java or Python
- Big-O analysis
- Recursion and call stack
- Basic maths for coding
- Constraint estimation
Project: Build a small benchmark tool that compares linear search, binary search and sorting times.
- Two pointers
- Sliding window
- Prefix sums
- Hash maps and sets
- String manipulation
Project: Create a plagiarism checker that compares documents using hashing and sliding window shingles.
- Linked lists
- Stacks and queues
- Monotonic stack
- Deque
- Expression evaluation
Project: Implement a text editor buffer with undo and redo using stacks and a linked list.
- Tree traversals
- Binary search trees
- Tries
- Heaps and priority queues
- Greedy algorithms
Project: Build an autocomplete service using a trie with top suggestions ranked by a heap.
- BFS and DFS
- Shortest paths
- Topological sort and Union-Find
- 1D and 2D DP
- Knapsack and subsequence DP
Project: Create a metro route planner using BFS and Dijkstra with fare and time options.
- Merge and quick sort
- Binary search on answer
- Backtracking
- Timed contests
- Mock interviews
Project: Solve and document 150 mixed problems by pattern in a public GitHub repository.
Practise each topic
Frequently asked questions
How long does it take to learn Data Structures and Algorithms?
Following this roadmap takes about 16 weeks with regular practice. Working professionals usually need a little longer.
What should I learn first in Data Structures and Algorithms?
Start with phase 1: Language basics in Java or Python, Big-O analysis, Recursion and call stack. Build the phase project before moving on.
How do I know I am job-ready in Data Structures and Algorithms?
When you can finish all phase projects on your own, solve the medium questions in the topic sheets and clear the mock interview comfortably.