The course is intended to provide a hands-on introduction to machine learning for applications in molecular sciences. Machine learning continues to provide new tools to enhance research in all subfields of chemistry. This course aims to acquaint the participant with a range of machine learning techniques that are used for chemical research and provide hands-on experience with developing, training, applying, and analysing machine learning software. The course starts with an introduction to programming in python and a general introduction to machine learning, and continues with topics including chemical language models, Bayesian optimisation and generative AI for molecular design. The course takes seven full days, spread over the period from April 8th until May 1st, with each day featuring lectures in the morning and a practicum in the afternoon. The practicum requires the participant to bring a modern laptop with an installation of micromamba (or equivalent, such as conda) and vscode for source code development in python.