Intro to Algorithms

Catalog description

This course is an introduction to the design and analysis of algorithms, and covers several basic algorithmic paradigms and their application to core computational problems in graph theory and optimization, as well as analysis of time and space complexity. The primary focus of the course will be on understanding the divide-and-conquer, greedy and dynamic programming paradigms for algorithm design as well as the problem areas to which they can be applied. Example application areas include graph theory, discrete optimization, numeric and scientific computing and machine learning. Topics usually include: asymptotic analysis and big-O notation; divide-and-conquer algorithms; recurrences and the master method; greedy algorithms; graph algorithms (Breadth-First Search, Depth-First Search, Connectivity and Shortest Paths); dynamic programming; linear programming; lower bounds and computational complexity.