Module 4:
Data Visualization
Live Webcast | Thursday, September 3, 2026 | 9:30 to 12:30AM EDT
Seeing data before and after modeling, and telling stories with it. Exploratory plots, high-dimensional visualization, uncertainty display, and communicating results to scientific and engineering audiences. The focus is on using AI tools such as Claude to do this faster: generating and refining plots from a description, building interactive views without hand-writing plotting code, and iterating on a visualization in seconds rather than hours. Visualization is a debugging tool for both data and models, used to catch problems that summary statistics hide.
MODULE 1:
Introduction to AI Agents
Live Webcast
August 31, 2026
9:30 to 12:30AM EDT
MODULE 2:
AI Coding for Non-CS
Live Webcast
September 1, 2026
9:30 to 12:30AM EDT
COURSE INFORMATION
AI tools have reached the point where a scientist or engineer with no background in computer science can build real, working systems.
Over five sessions, participants will learn to put AI agents to work automating routine tasks, build reliable software with AI copilots, acquire and clean real-world data, visualize and communicate results, and adapt foundation models to their own problems.
The course is designed for people outside of AI and CS who want practical capability rather than theory. No prior coding experience is assumed. Each session is built around interactive training and application; participants will leave with the skills to apply these tools to their own research and engineering.
INSTRUCTORS
Wojciech Matusik is the Cadence Design Systems Professor of Electrical Engineering and Computer Science at MIT, with appointments in EECS and Mechanical Engineering. He leads the Computational Design and Fabrication Group at CSAIL, where his research spans computational design, computer graphics, applied machine learning, and digital fabrication. He received his B.S. from UC Berkeley and his M.S. and Ph.D. from MIT, and his work has been recognized with honors including a Humboldt Research Award, a DARPA Young Faculty Award, an ACM SIGGRAPH Significant New Researcher Award, and a Sloan Research Fellowship.
Hanspeter Pfister is the An Wang Professor of Computer Science at the Harvard John A. Paulson School of Engineering and Applied Sciences and an affiliate faculty member of the Center for Brain Science. His research in visual computing lies at the intersection of scientific visualization, information visualization, computer graphics, and computer vision, spanning biomedical image analysis, image and video analysis, and visual analytics in data science. He holds a Ph.D. in computer science from Stony Brook University and an M.S. in electrical engineering from ETH Zurich, and before joining Harvard he spent over a decade at Mitsubishi Electric Research Laboratories. He is a recipient of the IEEE Visualization Technical Achievement Award and served as technical papers chair for SIGGRAPH 2012.