25 courses with the subject COMP, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
COMP 141Programming Fundamentals
DATA 242: Program Design and Data Structures for Data Analytics or COMP 241: Data Structures and Algorithms DATA 244/MATH 244: Introduction to Data Analytics and Visualization DATA 344/COMP 344/MATH 344: Advanced Methods in Data Analytics
Credits: An introduction to writing computer-verified software and proving mathematical theorems using dependent types. Students will learn to write code using a dependently-typed functional programming language, both to create programs with built-in proofs of correctness and to prove mathematical truths. A main theme of the course is the connection between types and programs on one hand, and propositions and proofs on the other. Other topics include functional programming, algebraic datatypes, and constructive logic. Students who do not meet the COMP 142 prerequisite but have other forms of programming experience are encouraged to reach out to the instructor about enrolling in the course.
Credits: This course is an introduction to reinforcement learning (RL) and sequential decision problems. Students will learn about RL’s agent-environment interface, Markov decision processes, multi-armed bandits, dynamic programming, Monte Carlo methods, temporal-difference learning, and eligibility traces. Students will learn about the differences between model-free and model-based methods, and the trade-off between exploration and exploitation. While the course is aimed at giving students a solid foundation in tabular solution methods for reinforcement learning, the course will also provide a high-level overview of RL with function approximation using neural networks. Students will be required to complete several programming assignments and a final project. Computer Science Applications Elective
