• Engineers
• Technicians
• Data Analysts
• Scientists
• Project Managers

Participants in this course will learn the fundamental concepts of simulation engineering, including how to develop and implement simulation models, analyse simulation data, and use simulation software tools.

With a mix of theoretical basics and practical exercises, participants will be able to plan and carry out simulation projects independently. The course is aimed at beginners with no prior knowledge of simulation but is also suitable for those wishing to expand their knowledge in this fast-growing and increasingly important field. Large technology companies and innovative start-ups are increasingly relying on simulation technologies, making this course a valuable step in your professional development.

After completing the module, students will be able to:

• assess the applicability and usefulness of the simulation method given a specific modelling situation
• list and define typical quantitative objectives for process simulations
• describe and evaluate processes systematically and quantitatively
• implement simple models in a professional simulation environment

The module covers the following topics:

1. simulation as an experiment-based method for evaluating complex processes
2. questions, goals, and objectives for simulation
3. theoretical fundamentals of
4. the structure of a simulation project
5. introduction to modelling processes
6. first steps with simulation, verification, and validation
7. basics of process improvement and experiment design
8. introduction to the simulation environment Simio

This module is part of the CAS in Digital Life Sciences continuing education programme, but can also be attended independently of the CAS. Credit points earned for this module can be credited to the CAS course at a later date, provided the relevant general conditions are fulfilled.

More information here: CAS in Digital Life Sciences

You can find an overview of our continuing education programmes in the field of computational science and artificial intelligence here.

The module will consist of lectures and practical exercises. In addition to lectures, participants will be required to self-study selected topics. Also, participants will work in groups on a simulation project and present their results at the end of the course. 

• Project work: 50%
• Final presentation: 50%

Three weekly lessons are scheduled for Thursday evenings. Participants will start working on their final project in the second week. The project presentations will take place in the last session.

• No entry requirements
• No prerequisites necessary