1. Bubble Sort: Repeatedly swaps adjacent elements if they are in the wrong order.

2. Selection Sort: Repeatedly selects the smallest element and swaps it with the current position.

3. Insertion Sort: Builds the sorted array one item at a time by repeatedly inserting the next item into its proper place.

4. Merge Sort: A divide-and-conquer algorithm that splits the array into halves, sorts each half, and then merges them back together.

5. Quick Sort: A divide-and-conquer algorithm that selects a pivot and partitions the array around the pivot, recursively sorting the partitions.

6. Heap Sort: Uses a binary heap data structure to sort elements.

7. Radix Sort: Non-comparative integer sorting algorithm that sorts by processing individual digits.

Searching Algorithms

8. Linear Search: Sequentially checks each element until the target is found or the list ends.

9. Binary Search: Efficiently finds the target in a sorted array by repeatedly dividing the search interval in half.

Graph Algorithms

10. Depth-First Search (DFS): Explores as far as possible along each branch before backtracking.

11. Breadth-First Search (BFS): Explores all neighbors at the present depth prior to moving on to nodes at the next depth level.

12. Dijkstra's Algorithm: Finds the shortest path between nodes in a graph with non-negative weights.

13. Bellman-Ford Algorithm: Computes shortest paths from a single source vertex to all other vertices in a graph with negative weights.

14. Floyd-Warshall Algorithm: Finds shortest paths between all pairs of vertices.

15. Prim's Algorithm: Finds the minimum spanning tree for a weighted undirected graph.

16. Kruskal's Algorithm: Finds the minimum spanning tree by sorting all edges and adding them one by one.

Tree Algorithms

17. Binary Tree Traversal (In-order, Pre-order, Post-order): Various methods to traverse a binary tree.

18. Binary Search Tree (BST) Insertion/Deletion: Operations to maintain the BST property.

19. AVL Tree: A self-balancing binary search tree.

20. Red-Black Tree: A balanced binary search tree with additional properties to ensure balance.

21. Segment Tree: A tree used for storing intervals or segments.

22. Fenwick Tree (Binary Indexed Tree): A tree structure to provide efficient methods for cumulative frequency tables.

Dynamic Programming

23. Knapsack Problem: Finds the most valuable combination of items that fit in a knapsack of a given capacity.

24. Longest Common Subsequence (LCS): Finds the longest subsequence present in both given sequences.

25. Longest Increasing Subsequence (LIS): Finds the longest increasing subsequence in a given sequence.

26. Fibonacci Sequence: Computes the nth Fibonacci number.

27. Matrix Chain Multiplication: Determines the most efficient way to multiply a given sequence of matrices.

28. 0/1 Knapsack Problem: A specific case of the knapsack problem where each item can be taken or left.

Greedy Algorithms

29. Activity Selection Problem: Selects the maximum number of activities that don't overlap.

30. Huffman Coding: Constructs a prefix-free binary tree for optimal encoding.

31. Job Sequencing Problem: Schedules jobs to maximize profit.

String Algorithms

32. KMP Algorithm: Searches for occurrences of a pattern within a text using a partial match table.

33. Rabin-Karp Algorithm: Searches for pattern occurrences using hashing.

34. Longest Palindromic Substring: Finds the longest substring which is a palindrome.

35. Z Algorithm: Finds all occurrences of a pattern in a text.

Miscellaneous Algorithms

36. Union-Find (Disjoint Set): Tracks and merges disjoint sets.

37. Topological Sort: Linear ordering of vertices in a directed acyclic graph (DAG).

38. Trie: A tree-like data structure used to store a dynamic set of strings.

39. Bit Manipulation: Various algorithms that use bitwise operations.

40. Reservoir Sampling: A random sampling algorithm for unknown or very large data sets.

41. Bloom Filter: A space-efficient probabilistic data structure used to test whether an element is a member of a set.

Number Theory

42. Sieve of Eratosthenes: Finds all prime numbers up to a given limit.

43. Euclidean Algorithm: Computes the greatest common divisor (GCD) of two integers.

44. Modular Exponentiation: Computes \(a^b \\mod c\) efficiently.

45. Chinese Remainder Theorem: Solves systems of simultaneous congruences.

Advanced Data Structures

46. Hash Tables: Maps keys to values using a hash function.

47. Priority Queue: A data structure where each element has a priority, and the highest priority element is served first.

48. B-Tree: A self-balancing tree data structure that maintains sorted data and allows searches, sequential access, insertions, and deletions.

49. Skip List: A data structure that allows fast search within an ordered sequence of elements.

Computational Geometry

50. Convex Hull: Finds the smallest convex polygon that can contain all the given points.