Wednesday, November 13th (14:00 – 18:00 CET)
Advanced Course (Day 1): Multivariate Data Analysis (MVDA) Methods
14:00 – 14:30
Introduction of the lecturing team and participants
14:30-15:30
Motivation for MVDA and process data specialties
15:45 – 17:00
PCA and Missing Data Handling
17:00 – 18:00
Hands-on Experience & Industrial Use Cases
Thursday, November 14th (14:00 – 18:45 CET)
Advanced Course (Day 2): Advanced MVDA Methods
14:00 – 14:45
Multivariate regression – MLR, PCR, PLSR
14:45 – 15:45
PLS2 and Variable Importance
16:00 – 16:50
Decision Trees, Software Landscape for process digitalization
16:50 – 17:30
Why do we need non-linear process models?
17:30 – 18:45
Hands-on Experience & Industrial Use Cases
Friday, November 15th (14:00 – 18:30 CET)
Advanced Course (Day 3): Machine Learning (ML) Methods
14:00 – 15:00
Introduction to Machine Learning
15:00 – 16:00
Examples of Machine Learning tools
16:15 – 17:30
Gaussian Processes
17:30 – 18:30
Hands-on Experience & Industrial Use Cases
Wednesday, November 20th (14:00 – 18:30 CET)
Advanced Course (Day 4): Combination of Data- and Knowledge-driven Approaches
14:00 – 15:00
Basic Principles of Hybrid Models
15:15 – 16:45
Examples of Hybrid Models (USP and continuous processes)
17:00 – 18:30
Hands-on Experience & Industrial Use Cases
Thursday, November 21st (14:00 – 18:15 CET)
Advanced Course (Day 5): Applications of Smart Digital Solutions in Bioprocessing
14:00 – 14:30
Digital Twins in bioprocessing
14:30 – 15:30
Examples of Hybrid Models (DSP)
15:45 – 17:00
Machine Learning models for Spectral Data, Kalman and Particle Filters
17:00 – 18:15
Hands-on Experience & Industrial Use Cases
Friday, November 22nd (14:00 – 18:45 CET)
Advanced Course (Day 6): Smart Digital Solutions to Support Decision Making
14:00 – 14:45
Bayesian Inference and Model-based Experimental Design
14:45 – 15:30
Application for Parallel and Robotic reactor systems
15:30 – 16:15
Robustness analysis and Model-based Process Optimization
16:30 – 18:30
Mini Hackathon
18:30 – 18:45
Feedback & Certificates