1. Sorting Algorithms:

2. • Bubble Sort
   • Insertion Sort
   • Selection Sort
   • Merge Sort
   • Quick Sort
   • Heap Sort
   • Counting Sort
   • Radix Sort

3. Searching Algorithms:

   • Linear Search
   • Binary Search

4. Graph Algorithms:

   • Breadth-First Search (BFS)
   • Depth-First Search (DFS)
   • Dijkstra’s Algorithm (Shortest Path)
   • Kruskal’s Algorithm (Minimum Spanning Tree)
   • Prim’s Algorithm (Minimum Spanning Tree)

5. Dynamic Programming Algorithms:

   • Fibonacci Series
   • Longest Common Subsequence
   • Knapsack Problem

6. Divide and Conquer Algorithms:

   • Binary Search
   • Merge Sort
   • Quick Sort

7. Greedy Algorithms:

   • Knapsack Problem
   • Huffman Coding
   • Dijkstra’s Algorithm (Greedy version)

8. Backtracking Algorithms:

   • N-Queens Problem
   • Sudoku Solver

9. Computational Geometry Algorithms:

   • Convex Hull (e.g., Graham Scan)

10. String Algorithms:

    • Pattern Matching (e.g., Naive algorithm, Rabin-Karp, Knuth-Morris-Pratt)

11. Number Theory Algorithms:

    • Euclidean Algorithm (GCD)
    • Sieve of Eratosthenes (Prime numbers)

Remember, Python’s simplicity and readability make it an excellent choice for understanding, prototyping, and implementing various algorithms. If you are looking to dive deeper into specific algorithms, you can find a wealth of resources and examples online, as well as textbooks dedicated to algorithms and data structures. Happy coding!