Advanced Course (Day 1)
Monday, June 15
09:00 – 12:40 CET
Multivariate Process Data Analysis (MVDA) Methods
09:00 – 09:30
Introduction of the Lecturing Team and Participants
09:30 – 10:15
Motivation for Process Models and Process Data Specialties
10:15 – 10:45
Roles of Process Models
11:00 – 11:45
Data Unfolding and PCA
11:45 – 12:30
Hands-on Experience & Industrial Use Cases
13:30 – 18:00 CET
Advanced MVDA and Intro to Machine Learning (ML)
13:30 – 14:15
MLR, PCR, PLSR
14:15 – 15:00
PLS2 and Variable Importance
15:15 – 16:30
Introduction to Machine Learning
16:45 – 18:00
Hands-on Experience & Industrial Use Cases
18:30 –
Social Program
Advanced Course (Day 2)
Tuesday, June 16
09:00 – 12:30 CET
ML Method & Knowledge Support
09:00 – 10:15
Examples of Machine Learning Tools
10:15 – 11:15
Gaussian Processes
11:30 – 12:30
Basic Principles of Hybrid Models
13:30 – 18:00 CET
Hybrid Modeling
13:30 – 14:30
Hands-on Experience & Industrial Use Cases
14:30 – 15:30
Industrial Examples of Hybrid Models – USP
15:45 – 16:45
Industrial Examples of Hybrid Models – DSP
17:00 – 18:00
Hands-on Experience & Industrial Use Cases
18:30 –
Social Program
Advanced Course (Day 3)
Wednesday, June 17
09:00 – 12:30 CET
Applications of Smart Digital Solutions in Bioprocessing
09:00 – 10:00
Bayesian Optimization for Experimental Design
10:00 – 10:45
Predictive Spectral Modeling
11:00 – 11:45
Digital Twins & Real Time Applications
11:45 – 12:30
Hands-on Experience & Industrial Use Cases
12:30 – 12:40
Feedback & Certification