Machine Learning in Chemical Engineering


Digitalization transforms the chemical industry across its horizontal value chain. Machine learning can be used to tackle a wide range of chemical-engineering problems. There is not any “one-size-fits-all” machine-learning algorithm that can solve all problems. Certain conditions have to be met to solve problems using machine learning.

Target group 

Chemical Engineers working in R&D, production engineering or process engineering.

Total scope 
2 days
No. of seats 
Course language 
Course brochure 
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Entry requirements 

Basic knowledge in mathematics and statistics.


This course explains what can be done with AI and what is required to use AI. The course provides insight to how calculations are done behind the scene. You learn the topic through a blend of lectures and worked-through examples from the chemical-engineering field. Lectures illustrate how AI is integrated into R&D and production of materials. At the end of the course, you learn how to create predictive models in cases where physiochemical modelling is not feasible. We have selected computer exercises from systems relevant to Chemical Engineers working within research, development and production. The exercises are prepared in a way to minimize programming to allow you more time to focus on interpreting the quality of the results.

Cancellation policy: 

This is just a declaration of interest, not a firm application.