Introduction:
Data structure and algorithms are the building blocks of computer science and play a vital role in software development. They are essential in solving complex problems efficiently and effectively. A strong foundation in data structures and algorithms is critical for any aspiring computer scientist or software engineer. In this list, we have compiled the most essential topics that you should learn to get started with data structures and algorithms from scratch.
Data Structures
- Arrays
- Linked Lists
- Singly Linked Lists
- Doubly Linked Lists
- Circular Linked Lists
- Stacks
- Queues
- Hash Tables
- Trees
- Binary Trees
- Binary Search Trees
- AVL Trees
- Red-Black Trees
- B-Tree Trees
- Heaps
- Min-Heap
- Max-Heap
- Graphs
- Directed Graphs
- Undirected Graphs
- Weighted Graphs
- Unweighted Graphs
Algorithms
- Searching Algorithms (Linear and Binary Search)
- Sorting Algorithms (Bubble Sort, Insertion Sort, Selection Sort, Merge Sort, Quick Sort, Heap Sort)
- Recursive Algorithms
- Greedy Algorithms
- Dynamic Programming
- Backtracking
- Divide and Conquer
- Breadth-First Search (BFS)
- Depth-First Search (DFS)
- Dijkstra’s Algorithm (Shortest Path)
- Bellman-Ford Algorithm (Shortest Path)
- Kruskal’s Algorithm (Minimum Spanning Tree)
- Prim’s Algorithm (Minimum Spanning Tree)
Miscellaneous Topics
- Time and Space Complexity
- Big-O Notation
- Recursion and Iteration
- Analysis of Algorithms
- Algorithm Design Techniques
- NP-Completeness and Approximation Algorithms
Conclusion:
Learning data structures and algorithms is a journey that requires patience, practice, and a strong foundation. This list of topics provides a comprehensive guide to help you get started with data structures and algorithms from scratch. As you progress through your learning journey, remember to keep practicing and applying your knowledge to real-world problems. With dedication and hard work, you can master data structures and algorithms and become a skilled programmer.