Teaching

Courses

Course materials are on GitHub, one repository per term.

  1. Fall 202606-763 / 14-763 / 18-763 Systems & Toolchains for AI in Engineering course site materials
  2. Spring 202606-642 Data Science and Machine Learning in Chemical Engineering materials
  3. Spring 202606-643 Scientific Software Engineering with AI Coding Agents materials
  4. Fall 202506-623 / 06-713 Mathematical Modeling of Chemical Engineering Processes materials
  5. Spring 202506-623 / 06-713 Mathematical Modeling of Chemical Engineering Processes materials
  6. Spring 202406-642 Data Science and Machine Learning in Chemical Engineering materials
  7. Spring 202406-643 Scientific Software Engineering materials
  8. Fall 202306-623 Mathematical Modeling of Chemical Engineering Processes materials
  9. Spring 202206-681 Data Visualization and Modeling materials
  10. Fall 202106-623 Mathematical Modeling of Chemical Engineering Processes materials
  11. Spring 202006-681 Data Science and Machine Learning in Chemical Engineering materials
  12. Fall 201906-623 Mathematical Modeling of Chemical Engineering Processes materials
  13. Fall 201806-623 Mathematical Modeling of Chemical Engineering Processes materials
  14. Spring 201706-364 Chemical and Reaction Engineering materials
  15. Fall 201606-625 Chemical and Reactive Systems materials
  16. Spring 201606-640 Molecular Simulation materials
  17. Fall 201506-625 Chemical and Reactive Systems materials

Open course materials

pycse: Python Computations in Science and Engineering
A book on using Python for scientific and engineering computation, from numerical methods and ODEs to optimization and data analysis. Source on GitHub.
Modeling Materials Using Density Functional Theory
A guide to computational materials science with DFT, VASP and the Atomic Simulation Environment (ASE). Source on GitHub.
Claude-Light
A remotely accessible instrument for learning about running experiments, data analysis, automation and design of experiments.