Algorithms Course Index – Dataplexa

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Algorithms Course Index

A complete Algorithms roadmap — covering foundations, classical algorithms, dynamic programming, graph theory, trees, hashing, and modern AI algorithms. Designed for interviews, academics, and real-world projects.

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I. Foundations & Complexity (16 Lessons)

1. Introduction to Algorithms 2. Time & Space Complexity 3. Big-O, Theta, Omega 4. Mathematical Analysis 5. Recursion Fundamentals 6. Basic Sorting Techniques 7. Merge Sort 8. Quick Sort 9. Heap Sort 10. Counting & Radix Sort 11. Linear Search 12. Binary Search 13. Divide & Conquer Strategy 14. D&C in Searching 15. D&C in Sorting 16. Master Theorem

II. Classical Algorithms (12 Lessons)

17. Greedy Strategy Intro 18. Activity Selection 19. Fractional Knapsack 20. Huffman Coding 21. Dijkstra’s Algorithm 22. DP Introduction 23. Memoization vs Tabulation 24. Fibonacci & Coin Change 25. LCS Problem 26. LIS Problem 27. 0/1 Knapsack 28. DP in Optimization

III. Graphs & Trees (13 Lessons)

29. Graph Basics 30. BFS 31. DFS 32. Cycle Detection 33. Topological Sorting 34. MST – Prim 35. MST – Kruskal 36. Bellman–Ford 37. Binary Trees 38. BST 39. AVL Trees 40. Tries 41. Segment Trees

IV. Modern Algorithms (9 Lessons)

42. Hash Tables 43. Collision Handling 44. Hashing Applications 45. Gradient Descent 46. Stochastic & Mini-Batch GD 47. ADAM & RMSProp 48. A* Search Algorithm 49. Uniform Cost Search 50. Hill Climbing & Simulated Annealing