Digitalization transforms the chemical industry across its horizontal value chain. Data Analytics can be used to improve your processes.
This two-day course is intended for process engineers working in R&D, production engineering or process engineering.
Basic knowledge in mathematics
This course explains the importance of experimental design to efficiently plan your experiments and how maximum amount of information is retrieved by using minimum resources. The course introduces the most central data-analysis methods including linear and non-linear regression, logistic regression, multivariate data analysis including principal component analysis (PCA) and PLS regression. The final part of the course presents advanced data analysis methods such as neural networks by use of worked-through examples.
This course prepares you for the upcoming (more advanced) course Machine Learning in Chemical Engineering, in which you do supervised hands-on computer exercises in computer rooms at Chalmers.
This is just a declaration of interest, not a firm application.