Data Structures & Algorithms Roadmap
Master the fundamentals of computer science through this structured learning path.
Phase 1: Foundations
Arrays & Strings
- Basic array operations
- String manipulation
- Two-pointer technique
- Sliding window problems
Practice Problems:
Linked Lists
- Singly linked lists
- Doubly linked lists
- Fast and slow pointers
- Cycle detection
Stacks & Queues
- Stack implementation
- Queue implementation
- Monotonic stack
- Priority queues
Phase 2: Intermediate Structures
Trees
- Binary trees
- Binary search trees
- Tree traversals (inorder, preorder, postorder)
- Level-order traversal
Heaps
- Min heap and max heap
- Heap operations
- Top K problems
- Median finding
Hash Tables
- Hash map implementation
- Hash set usage
- Collision handling
- Frequency counting
Phase 3: Advanced Topics
Graphs
- Graph representations
- BFS and DFS
- Shortest path algorithms
- Topological sort
Dynamic Programming
- Memoization
- Tabulation
- Common patterns
- Optimization problems
Advanced Algorithms
- Divide and conquer
- Backtracking
- Greedy algorithms
- Bit manipulation
Resources
- Books: Introduction to Algorithms by CLRS
- Online: LeetCode, HackerRank, Codeforces
- Videos: MIT OpenCourseWare, Abdul Bari
Timeline
Estimated completion: 3-6 months with consistent practice (1-2 hours daily)