Xiaoyun Fu

An introduction to computational problem solving designed to give an overview of computer science using real-world problems across a broad range of disciplines. Students learn how to think about these problems and how to structure effective solutions to them using computation. No programming knowledge is required or expected; students learn how to implement their solutions in Python. The in-person and online sections are exactly the same class, covering the same material in same way, on the same daily class meeting schedule, except that the online section meets online.

Algorithms are the engines of a great majority of systems, natural and artificial alike. This course introduces algorithmic thinking as a discipline for reasoning about systems, taming their complexities, and elucidating their properties. Algorithmic techniques, along with their correctness and efficiency, will be taught through reasoning about systems of interactions, such as markets, that are ubiquitous in our highly connected world.

Methods for designing and analyzing computer algorithms and data structures. The focus of this course will be on the theoretical and mathematical aspects of algorithms and data structures. Cross-list: ELEC 512. Recommended Prerequisite(s): STAT 310 or ECON 307 or STAT 331 or ELEC 331 or ELEC 303 or STAT 312

Methods for designing and analyzing computer algorithms and data structures. The focus of this course will be on the theoretical and mathematical aspects of algorithms and data structures. Cross-list: COMP 582. Recommended Prerequisite(s): STAT 310 or ECON 307 or STAT 331 or ELEC 331 or ELEC 303 or STAT 312