About the Course

Modern computational methods like machine learning and mathematical optimization let you design novel interactive technologies. This Human-Computer Interaction (HCI) course will introduce you to the basics of such computational methods and guide you in learning how to apply them to design interfaces and interaction methods.

This course omits some essential topics in HCI, such as:

We do not discuss user-centered design for designing technologies. That is, we do not cover topics like prototyping techniques like paper prototyping and Wizard-of-Oz. We also do not discuss design methodologies, i.e., “how” we create technologies. Instead, we focus on computational techniques for developing and evaluating technologies.
Likewise, this course does not cover empirical methodologies in HCI. If you are interested in qualitative methods like user interview and quantitative methods like A/B testing, you should refer to: IS211 Interaction Design and Prototyping.
The course does not focus on making hardware user interfaces. Thus, if you are interested in learning about sensors, actuators, circuit design, and other hardware-related aspects of HCI, this course is not for you.

There are some prerequisites:

Good programming skills. We use Python in this course, so being able to use the language would help.
Undergraduate-level knowledge in linear algebra, calculus, probability, and statistics.
(Recommended) Exposure to HCI research and user-centered design. Although the course will focus on computational aspects of HCI, having a basic understanding of general HCI concepts would help. If you are unfamiliar with such topics, see the lecture notes in the following page: IS211 Interaction Design and Prototyping).

Details

Please bring your laptop every week. Every lecture involves some hands-on programming activities.

Lecturer: Kotaro Hara ([email protected], 6828 9691, SCIS1 4047)
TA:
- Smitha Sheshadri ([email protected])
- Ma Xiao ([email protected])
Class Time: Tuesday 7:00-10:15PM
Class Location: SCIS1 Seminar Room 3.3