The course covers the effective use of computers in working with analytical and data-driven models from chemistry, physics and engineering. Key topics are:

• the interplay of computers, data and mathematics,
• the Python programming language for data processing and visualization,
• working with data and basic statistics,
• ordinary and partial differential equations (ODEs and PDEs) for modeling in chemistry, physics and engineering,
• solving ODEs and PDEs with Python, including parameter estimation problems
• methods for data-driven modeling (linear regression, artificial neural networks and others)
• the interplay of classical and data-driven modeling.