Roadmap/Algorithms
Intermediate to Advanced

Algorithms

Develop deep problem-solving skills by understanding the core algorithmic techniques that power all modern software systems — from sorting to dynamic programming.

10–12 weeks
13.8k students
4.9 rating
Progress0/55 lessons

Key Topics You'll Master

1
Algorithm Foundations & Complexity
2
Recursion and Iteration
3
Sorting Algorithms
4
Searching Algorithms
5
Divide and Conquer
6
Greedy Algorithms
7
Dynamic Programming (DP)
8
Graph Algorithms
9
String and Pattern Algorithms
10
Optimization and Real-World Applications
Learning Outcomes
  • Understand time and space complexity deeply (Big O, Omega, Theta)
  • Analyze, design, and optimize algorithms for efficiency
  • Master recursion, iteration, and problem decomposition
  • Apply algorithmic paradigms like divide & conquer, greedy, and dynamic programming
  • Work with real-world graph, string, and numeric problems
  • Develop competitive programming and interview problem-solving skills
Prerequisites
  • Basic programming knowledge (in any language)
  • Understanding of data structures (arrays, lists, trees, graphs)
  • Basic math and logic reasoning
1
Algorithm Foundations & Complexity
Understanding performance, analysis, and algorithm behavior.
1 week
What is an Algorithm?
video • 15 min
Time & Space Complexity (Big O, Ω, Θ)
video • 25 min
Asymptotic Analysis and Growth Rates
video • 20 min
Common Complexity Classes (O(1), O(n), O(n log n), O(2^n))
article • 15 min
Practice: Analyze and Compare Algorithms
exercise • 45 min
2
Recursion and Iteration
Breaking problems into smaller subproblems using recursion.
1.5 weeks
Understanding Recursion and Stack Frames
video • 25 min
Tail Recursion and Optimization
video • 20 min
Recurrence Relations and Subproblem Trees
video • 22 min
Iterative vs Recursive Trade-offs
article • 15 min
Practice: Factorial, Fibonacci, Tower of Hanoi
exercise • 55 min
3
Sorting Algorithms
Organizing data efficiently through comparison-based and non-comparison-based methods.
1.5 weeks
Bubble, Insertion, and Selection Sort
video • 25 min
Merge Sort (Divide and Conquer)
video • 25 min
Quick Sort and Partition Logic
video • 25 min
Counting, Radix, and Bucket Sort
video • 20 min
Sorting Stability and In-Place Concepts
article • 15 min
Practice: Sorting Visualizations and Comparisons
exercise • 60 min
4
Searching Algorithms
Efficiently locating elements or patterns in structured or unstructured data.
1 week
Linear Search and Basic Search Logic
video • 18 min
Binary Search (Iterative & Recursive)
video • 25 min
Ternary Search and Search Space Reduction
video • 20 min
Applications of Binary Search (Lower/Upper Bound)
article • 15 min
Practice: Search Problems on Arrays & Ranges
exercise • 50 min
5
Divide and Conquer
Breaking complex problems into independent subproblems.
1 week
Divide and Conquer Concept
video • 20 min
Case Studies: Merge Sort, Quick Sort, Binary Search
video • 22 min
Matrix Multiplication and Closest Pair Problem
video • 25 min
Master Theorem for Complexity Analysis
article • 15 min
Practice: Recursive Tree Analysis
exercise • 50 min
6
Greedy Algorithms
Making optimal local choices to reach a globally optimal solution.
1.5 weeks
Greedy Choice Property and Optimal Substructure
video • 22 min
Activity Selection and Interval Scheduling
video • 25 min
Huffman Encoding and Data Compression
video • 25 min
Minimum Spanning Tree (Kruskal’s & Prim’s overview)
video • 25 min
Greedy vs Dynamic Programming Comparison
article • 15 min
Practice: Greedy Problem Set
exercise • 55 min
7
Dynamic Programming (DP)
Solving problems by storing intermediate results to avoid recomputation.
2 weeks
Overlapping Subproblems and Optimal Substructure
video • 25 min
Memoization vs Tabulation Approaches
video • 25 min
1D DP: Fibonacci, Climbing Stairs, Min Cost Path
video • 25 min
2D DP: Knapsack, Subset Sum, LCS
video • 30 min
State Representation and Transitions
article • 15 min
Practice: DP Challenge Set
exercise • 75 min
8
Graph Algorithms
Algorithms for connected, directed, and weighted graph structures.
2 weeks
Graph Traversal: BFS and DFS
video • 25 min
Shortest Path: Dijkstra, Bellman-Ford, Floyd-Warshall
video • 30 min
Topological Sorting and DAGs
video • 25 min
Union-Find and Connected Components
video • 22 min
Minimum Spanning Trees (Kruskal’s and Prim’s)
video • 25 min
Practice: Graph-Based Challenges
exercise • 75 min
9
String and Pattern Algorithms
Efficient text and pattern manipulation algorithms.
1.5 weeks
String Matching Basics (Naive and Sliding Window)
video • 22 min
KMP Algorithm (Prefix Table Concept)
video • 25 min
Rabin-Karp and Rolling Hash
video • 25 min
Z-Algorithm and Prefix Functions
video • 22 min
Applications: Substring Search, DNA Matching, Logs
article • 15 min
Practice: String Problem Set
exercise • 55 min
10
Optimization and Real-World Applications
How algorithms shape performance and decision-making in real systems.
1 week
Approximation and Randomized Algorithms
video • 25 min
Cache Optimization and Space Efficiency
video • 20 min
Parallel Algorithms and MapReduce Basics
video • 25 min
Algorithm Design Patterns in Industry
article • 15 min
Capstone: Build and Analyze a Real-World Algorithm
exercise • 90 min