ME 5702: Data Science for Materials and Manufacturing

This course will provide students with data analytics skills for knowledge discovery and design optimization. The students will also learn how to apply data mining and machine learning techniques to tackle the challenges in manufacturing and computational materials engineering. Topics include basic concepts of supervised/unsupervised learning, design of experiments and data collection, material image processing, surrogate modeling, optimization and model calibration, multi-fidelity modeling, and applications of data analytics in manufacturing and computational materials engineering problems.

Credits

3

Offered

Spring 2027

Campuses

Storrs

Requirements

Undergraduate degree in engineering or computer science, departmental or unit consent required. Recommended preparation: Knowledge or coursework in probability and statistics. Ability to read, interpret and modify Python and MATLAB code. Ability to use Python and MATLAB for analyzing data for the course project.

Spring 2027 sections

Taught by Hongyi Xu.

Seats as of Nov 12, 2026. HuskyScheduler shows live seats when you search.

More courses

All ME courses (Mechanical Engineering) · All UConn subjects