The Machine Learning for Chemical Engineering course aims to provide trainees with the basic skills for creating and analysing complex datasets, applied to the field of Chemical Engineering.
Digital transformation is evolving rapidly, and the implementation of Industry 4.0 has led to an exponential increase in the use of digital sensors and thus the volume of data available. The emergence of Industry 5.0 reinforces this vision and requires the optimization of chemical processes through the application of advanced models of unit operations. At the same time, analysing large and complex datasets generated by chemical engineering research is becoming increasingly necessary. Therefore, in recent years, data science, and particularly machine learning, have experienced significant growth in various multidisciplinary areas, such as chemical engineering, chemistry, and bioengineering.
The objective of this course in Machine Learning for Chemical Engineering is to equip trainees with the fundamental technical skills to create and analyse complex datasets, enabling them to develop and apply machine learning models.
- Build and structure databases that are readable and usable by computers;
- Select and apply data science techniques to Chemical Engineering databases (laboratory or industrial), extracting the maximum amount of information;
- Critically analyse and develop machine learning models;
- Optimise the process in question based on the models developed.
Start Date: 11th September 2023
End Date: 15th September 2023
Schedule: Monday to Friday, 9.30 a.m. to 5.30 p.m.
Price for Students: 475€
Location: Alameda Campus
Applications are open until 21st August 2023