CS1699
SPECIAL TOPICS IN COMPUTER SCIENCE
FALLSPRINGSUMMER
PRE-REQ: This class is special and has channges each semester. Check the SCI website for information about it!
Course DescriptionThis is a special topics course that allows the computer science department to test run a course before deciding whether to permanently add it to our curriculum.
Spring 2026 topics:
CS 1699 (32717): Intro to Reinforcement Learning
Instructor: Emma Jordan
Description: Reinforcement learning is a branch of machine learning that focuses on learning to make decisions through trial and error. The course covers Markov decision processes, the mathematical formulation of sequential decision-making problems, and foundational reinforcement learning algorithms for making optimal decisions. Specifically, the course will cover value-based and policy gradient methods, such as Q-learning and actor-critic, which underpin modern successes, including playing Atari 2600 games, playing Go, and training large language models. The course will provide you with both the basic mathematical principles underlying these methods and programming experience by creating your own reinforcement learning agents. In addition to having programming skills of an upper-level undergraduate, you should also be familiar with differentiation, basic probability, and linear algebra concepts.
CS 1699 (29203): Design Thinking to Improve Work Practice - HONORS
Instructor: Jacob Biehl
Description: This is an interdisciplinary course intended for a broad range of students and/or backgrounds. The course seeks participation from technical, health, social science, business, and design-focused majors. The course targets students who want to experience early product exploration and prototyping processes while learning how to work successfully on a multidisciplinary team. The course will cover a range of design methodologies use to envision socio-technical solutions to improve workflow challenges. Each offering of the course will focus on a particular work domain. Spring 2026 semester will focus on home healthcare and clinical care processes. The course will investigate these domains using a variety of methods, which include ethnomethodological observations, contextual inquiry, structure interviews, cognitive walkthroughs, market discovery and more. Prototyping techniques include low-fidelity paper-based prototyping to use of modern design tools such as Figma and Adobe XD. Students will be expected to contribute significant time to reading, writing, and interaction with clinical partners.
CS 1699 (32711): Mobile Computing - HONORS
Instructor: Longfei Shangguan
Description: This course explores Mobile Computing, where continuous and seamless interaction is enabled by everyday mobile devices such as smart phones, watches, earphones, and smart glasses. We will provide the technical foundations for this paradigm by focusing on three key areas: principles of Sensing for gathering environmental context, efficient Computing techniques for low-power and continuous operation, and the deployment of intelligent On-Device AI models for context-aware decision-making. Through hands-on practical projects, you will learn how to design, build, and deploy innovative mobile systems that solve contemporary real-world problems.
Credits:3
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