The Design and Analysis of Algorithms course provides students with a comprehensive understanding of fundamental algorithmic techniques used to solve computational problems efficiently. The course emphasizes the principles of algorithm design, correctness, and performance analysis using mathematical and asymptotic techniques. Students will develop the ability to compare multiple algorithmic approaches and select appropriate solutions based on time and space complexity.
The course begins with Introduction to Algorithm Design, covering algorithmic fundamentals, asymptotic notations, complexity analysis, recurrence relations, and the evaluation of algorithm efficiency. It then explores the Divide and Conquer paradigm, including recursive problem solving, binary search, merge sort, quick sort, and related applications.
The third module focuses on Greedy and Dynamic Programming techniques, enabling students to solve optimization problems using greedy strategies and dynamic programming approaches. Topics include minimum spanning trees, shortest path algorithms, knapsack problems, matrix chain multiplication, and longest common subsequence.
