16-Data Structure and Algorithms
This Data Structures and Algorithms course provides a comprehensive exploration of core concepts crucial for efficient data management and problem-solving in computer science. Students will delve into fundamental data structures such as arrays, linked lists, stacks, queues, trees (including binary, AVL, and red-black trees), heaps, and hash tables, learning their operations, applications, and trade-offs. The course emphasizes algorithmic techniques, including various sorting methods (quick sort, merge sort), searching algorithms, and advanced topics like dynamic programming and greedy algorithms. Graph theory is covered extensively, with a focus on graph representation, traversal methods (DFS, BFS), shortest path algorithms (Dijkstra's, Bellman-Ford), and minimum spanning trees (Kruskal’s, Prim’s). Through theoretical lessons and practical coding exercises, students will develop skills in analyzing algorithm efficiency, implementing data structures, and solving complex computational problems. The course aims to build a solid foundation in designing efficient algorithms and optimizing performance across diverse applications.