Curriculum

In the 1st to 4th semesters, a total of 120 credits must be earned in the following subject areas:

Name Credits (ECTS)
Fundamentals 18
Modelling 18
Simulation and Validation 18
Visualization and Data Science 18
Electives 12
Project 12
Master Module 24

For each subject area, you will have a choice of up to nine modules which you can select according to your interests. In essence, this means that there are four areas of specialisation which you can pursue in a targeted manner in the context of the Digital Engineering Master's programme: Simulation Procedures, Data-based Procedures, Practical Engineering, or Practical Computer Science. In addition to your Master’s degree, you will receive proof of your completed courses in the form of a module overview. 

In the basic courses, you will learn to recognise and understand engineering issues, as well as how to formulate and implement them using mathematical methods. You will acquire the capability to implement mathematical descriptions and develop your own software using state-of-the-art algorithms and data structures.

The Fundamentals include the following modules: 

  • Algorithms and Datastructures
  • Applied Mathematics and Stochastics
  • Nonlinear Continuum Mechanics
  • Advanced Numerical Mathematics
  • Software Engineering
  • Statistics
  • Structural Dynamics
  • Structural Engineering Models
  • Object-oriented Modeling and Programming in Engineering

In the subject area of Modelling you will acquire comprehensive knowledge on how to generate and use models in engineering. The subject is spatial, temporal and functional modelling, as well as digital representation and application of models using standard software. You will also be shown options for mathematically describing and solving physical models and processes. In this context, techniques for optimising and identifying input and output variables are also taught.

Students may choose from the following modules:

  • 4- und 5D-Building Information Modeling (BIM)
  • Advanced Building Information Modeling
  • Advanced Modelling - Calculation
  • Collaborative Data Management
  • Computer models for physical processes – from observation to simulation
  • Introduction to Optimization/Optimization in Applications

The subject area of simulation and validation provides an introduction to the simulation of processes and structures. Special attention is given to handling stochastic input and output data, non-linear behaviour, and the use of efficient simulation methods. The models are validated using experimental data. In addition, methods of statistical experimental planning as well as measurement methods, subsequent signal processing and methods for system and parameter identification are presented.

Students may choose from the following modules:

  • Design and Interpretation of Experiments / Signal Processing
  • Extended Finite Elements and Mesh Free Methods
  • Linear FEM
  • Modelling of Steel Structures and Numerical Simulation
  • Nonlinear FEM
  • Process modelling and simulation in logistics and construction
  • Simulation Methods in Engineering
  • Stochastic Simulation Techniques and Structural Reliability
  • Fundamentals of Structural Health Monitoring (SHM) and Intelligent Structural Systems
  • Experimental Structural Dynamics

The subject area of Visualization and Data Science covers methods for visualising and analysing large sets of data. You will get to know methods and concepts for modular software development. Methods of image acquisition, image recognition, and image processing used to validate models and augment visualisations are also introduced.

Choose from the following modules:

  • Image Analysis and Object Recognition
  • Introduction to Machine Learning
  • Search-Based Software Engineering
  • Photogrammetric Computer Vision
  • Search Algorithms
  • Software Product Line Engineering
  • Visualization

Example programme schedules

Formal dependencies between modules