COMP 150-02 Assistive Algorithms

This course will focus on computational approaches to providing assistance to human users: sensing their behaviors, modeling their goals and plans, and intelligently choosing appropriate (including socially appropriate) actions. We will study these challenges through a series of case studies on state-of-the-art approaches to these problems, from smart prosthetics, to smart home assistants, to socially assistive robotics. This course requires some prior programming experience and an exposure to basic algorithms (ME 80 OR (COMP 15 and COMP/MATH 61) OR grad standing), and will focus on the practice of designing computational assistive systems, with a small project and skill-building through homework assignments and exams.

Please see the following list for the section number corresponding to the supervising faculty member.

COMP 150-02 Data Science for Sustainability

Crosslisted as ME 193. This course explores emerging topics in data science and statistical learning with applications to the three pillars of sustainability (environmental, economic, and social). Students learn to build, estimate, and interpret models that describe phenomena in the broad area of energy and environmental decision-making with an emphasis on social justice. Students leave the course as both critical consumers and responsible producers of data-driven analysis. The objectives of this class include i) learning a suite of data-driven modeling and prediction tools, ii) building the programming and computing expertise to use those tools, and iii) developing the ability to formulate an analysis to answer sustainability questions of interest to industry and/or government partners.