Day 1: Design of experiments
- Variation, noise and measurement systems
- Factorial and fractional factorial designs
- Response surface methods
- Hands-on: design a deposition study
Day 2: Applied machine learning
- Regression and surrogate models for small data
- Gaussian processes and uncertainty
- Bayesian optimization for sequential experiments
- Hands-on: optimize a simulated process
Format
On-site or remote. Exercises can use anonymized examples from your own process. Course materials are provided to each participant.
© 2026 Mina AI Labs LLC. General information only; not professional advice.