Advanced Course (Day 1)
Monday, June 17th
08:30 – 13:00 CET
Multivariate Data Analysis (MVDA) Methods
08:30 – 09:00
Introduction of the lecturing team and participants
09:00 – 09:45
Motivation for MVDA and process data specialties
10:00 – 11:00
PCA and missing data handling
11:00 – 11:15
Decision trees
11:15 – 12:30
Hands-on experience & industrial use cases
13:30 – 18:15 CET
Advanced MVDA Methods & Machine Learning (ML) Introduction
13:30 – 14:20
Multivariate regression – MLR, PCR, PLSR
14:20 – 14:50
PLS2 and variable importance
15:00 – 15:45
Why do we need non-linear process models?
15:45 – 16:45
Introduction to machine learning
17:00 – 18:15
Hands-on experience & industrial use cases
18:30 –
Apero at Hönggerberg
Advanced Course (Day 2)
Tuesday, June 18th
08:30 – 12:30 CET
Machine Learning (ML) Methods & Hybrid Modeling Intro
08:30 – 09:30
Examples of machine learning tools
09:30 – 10:15
Gaussian processes
10:30 – 11:30
Hands-on experience & industrial use cases
11:30 – 12:30
Basic principles of hybrid models
13:30 – 18:00 CET
Hybrid Modeling
13:30 – 16:00
Examples of hybrid models
16:15 – 17:00
Hybrid modeling quiz
17:00 – 18:00
Hands-on experience & industrial use cases
Advanced Course (Day 3)
Wednesday, June 19th
08:30 – 12:30 CET
Applications of Smart Digital Solutions in Bioprocessing
08:30 – 09:00
Digital twins in bioprocessing
09:00 – 09:40
Machine learning models for spectral data
09:50 – 10:20
Demo SpectraHow
10:20 – 11:00
Ensemble introduction
11:10 – 11:30
Kalman and particle filters
11:30 – 12:00
Bayesian Inference and model-based experimental design
12:00 – 12:30
Hands-on experience & industrial use cases
13:30 – 18:00 CET
Smart Digital Solutions to Support Decision Making
13:30 – 14:00
Application for parallel and robotic reactor systems
14:00 – 14:15
Intro in robustness analysis and model-based process optimization
14:15 – 17:15
Mini DataHowLab hackathon
17:15 – 18:00
Summary lecture
18:00 – 18:15
Feedback & certificates