Students learn important data structures in computer science and acquire fundamental algorithm design techniques to get the efficient solutions to several computing problems from various disciplines. Topics include the analysis of algorithm efficiency, hash, heap, graph, tree, sorting and searching, brute force, divide-and-conquer, decrease-and-conquer, transform-and-conquer, dynamic programming, and greedy programming.
The programming assignments of this course embraced a wide spectrum of topics and concepts, delving into fundamental calculations, user input manipulation, and intriguing tasks like proximity analysis, palindrome verification, and time difference calculations. Venturing further, these assignments challenged us with complex problems including generating diverse number combinations, refining sorting techniques, and implementing renowned algorithms like the Traveling Salesman Problem and Depth-First Search. Additionally, we used array manipulation, sorting algorithms, simulations of dynamic data structures, and advanced problem-solving techniques such as optimizing coin collection strategies on game boards and implementing the highly efficient Floyd algorithm for all-pairs shortest paths. Overall, these assignments served as a comprehensive exploration of algorithm programming, sharpening problem-solving skills and exposing us to a versatile toolkit for real-world algorithmic challenges.
