This course provides a practical introduction to the application of artificial intelligence (AI) and machine learning (ML) in chemistry, with a strong focus on industry-relevant examples such as property prediction, data analysis, and process optimization. Through hands-on exercises in a cloud-based Jupyter/Deepnote environment, participants will learn step by step how to explore datasets, build models, and interpret results using Python. No local installations are required, and all datasets used are free and openly available. Designed for chemists with no prior AI/ML or programming experience, the course emphasizes approachable workflows and real-world chemical applications. By the end of the course, participants will understand the benefits and limitations of AI/ML in chemistry and be equipped with practical skills to apply these methods in research and industrial contexts.
We are delighted to provide this online course, which will be across four afternoon sessions. Dates and times are as follows and set in UK Time (Greenwich Mean Time):
Monday, January 12 | 2.00 – 5.00pm GMT
Tuesday, January 13 | 2.00 – 5.00pm GMT
Monday, January 19 | 2.00 – 5.00pm GMT
Tuesday, January 20 | 2.00 – 5.00pm GMT
We are delighted to provide this online course, which will be across four afternoon sessions. Dates and times are as follows and set in UK Time (Greenwich Mean Time):
Monday, January 12 | 2.00 – 5.00pm GMT
Tuesday, January 13 | 2.00 – 5.00pm GMT
Monday, January 19 | 2.00 – 5.00pm GMT
Tuesday, January 20 | 2.00 – 5.00pm GMT
