The course on "Advanced Data Structures" provides students with a deep understanding of how to design and implement efficient data structures to solve complex computational problems. This course builds upon the foundation of basic data structures, such as arrays, linked lists, and trees, and covers more advanced data structures, such as graphs, heaps, hash tables, and tries. The course starts with a brief review of basic data structures, including their time and space complexities, and then moves on to more advanced data structures. Students will learn how to analyze the performance of data structures and how to select the appropriate data structure for a given problem. They will also learn how to implement these data structures using different programming languages, such as C++, Java, and Python. The course covers various topics, including:
- Graphs: This topic covers various graph algorithms, such as breadth-first search, depth-first search, shortest path algorithms, and minimum spanning tree algorithms. Students will also learn about the different representations of graphs, such as adjacency matrix and adjacency list.
- Heaps: This topic covers different heap data structures, such as binary heaps, binomial heaps, and Fibonacci heaps. Students will learn how to implement priority queues and heap sort algorithms using these data structures.
- Hash Tables: This topic covers the basics of hash tables, including hash functions, collision resolution techniques, and the analysis of hash table performance.
- Tries: This topic covers trie data structures, which are used for efficient string searching and storage. Students will learn how to implement trie data structures and different applications of tries.