Holistic applied AI in engineering – machine learning in production

The course “Machine Learning in Production” offers a practice-oriented introduction to the field of Machine Learning (ML) with a particular focus on engineering. To avoid common pitfalls in the successful application of ML, basic knowledge of ML methods and approaches to ML projects is required. This MOOC imparts knowledge of the fundamental concepts and functioning of the most important ML methods, as well as their application, through explanatory videos, practical examples, self-assessment tests and hands-on exercises.

• Insight into machine learning methods
• Application of ML techniques using Python scikit-learn
• Basic concepts for the correct implementation of machine learning

Upon completion of the course, you will be able to...

• explain different objectives – regression, classification, clustering, and outlier detection – and the corresponding ML methods.
• apply and compare ML methods for practical examples.
• implement ML projects in the engineering field.

• Prior knowledge in engineering sciences
• Basic knowledge of engineering mathematics
• Basic programming knowledge advantageous but not necessary