The aim of this course is to provide an overview and advanced insight into data analytics and modeling methodologies for process data. Fundamental concepts to visualize high-dimensional and highly correlated process and product quality data, to identify the important process drivers as well as to forecast the process and product quality behaviour will be presented in lectures. Hands-on and brainstorming sessions will be used to solve case studies from the (biopharmaceutical) industry. After the course the participants will be aware of relevant techniques and literature for process data analysis and will be able to evaluate different analysis paths for a given problem.
Ph.D., MBA, COO of DataHow & Lecturer at ETH Zurich
Michael is an expert in bioprocess modelling and regular speaker on the potential of smart digital pharma solutions on international conferences. He conducted his research in close collaboration with the pharma industry and co-authored more than 25 publications.
Ph.D., MBA, CEO of DataHow & Lecturer at ETH Zurich
Besides a long-standing research experience in polymer, separation and biotechnological processes, Alessandro has several years of experience in the pharma industry. He is a co-author of more than 70 publications and 4 patents.
Moritz von Stosch
Ph.D., CIO of DataHow
Moritz is one of the leading experts for hybrid modelling of bioprocesses. He combines an academic career path with several years of experience in the pharma industry. He is a co-author of more than 50 publications on microbial and mammalian upstream as well as downstream processing.
Further Lecturers and Tutors
Fabian Feidl, Ph.D., CTO of DataHow and bioprocess digitalization expert
Nicolas Cruz, Ph.D., modeling and automation expert
Prof. Massimo Morbidelli, thought lead bioprocessing
Adam Szalkowski, Ph.D., IT infrastructure expert
Martin Luna, Ph.D., DoE and optimization expert
Harini Narayanan, Ph.D. machine learning expert
The course takes the form of lectures, industry examples and case studies as well as hands-on sessions with software tasks (Different software packages will be provided to the participant). Supervisors and graduate assistants will support the participants during the interactive workshops and data analysis sessions. The course will be intense in content, interactive in learning and interdisciplinary in application and vision.
RECAP: 8th Advanced Process Data Analytics Course - April 2022