Our offerings
How to select what is right for you
Below, we give information on
- our Course Catalog and how to select from it
- the AISA Study Project
- the course Critically Reflecting in Intelligent Systems in Society (CRISS)
- and the Interdisciplinary AI Software Project.
Please check our overview graphics on this page, too.
Curriculum for MICRO, CAS and DAS
AISA Study Project (3 ECTS, MICRO & CAS & DAS)
The AISA Study Project takes place in the form of an AISA Hackathon. In the hackathon, participants will embark on an end-to-end journey of building a machine learning pipeline for a gaming application. Teams will start by collecting and preprocessing relevant in-game data, then use this dataset to train machine learning models tailored to enhance the gaming experience. Participants will perform inference, applying their models to real-time data. Finally, teams will present their findings, showcasing how their models improve gameplay dynamics, user engagement, or system efficiency. This event will provide hands-on experience with the full machine learning lifecycle, fostering creativity, collaboration, and technical skill development. The AISA Study Project is vital to all three certificates (MICRO, CAS, and DAS).
Course selection
Depending on the chosen type of certificate, you need to select the following number of courses:
- 1 course for a Microcredential (MICRO)
- 2 courses for a Certificate of Advanced Studies (CAS), out of which at least 1 compulsory course
- 4 courses for a Diploma of Advanced Studies (DAS), out of which at least 2 compulsory courses
- for CAS and DAS the course Critically Reflecting on Intelligent Systems in Society is obligatory (see below for details)
- for DAS the Interdisciplinary AI Software Project is obligatory (see below for details)
In the below course catalog, compulsory courses are labeled via COMPULSORY (use find-as-you-type to filter for them). Note that for the Microcredential (MICRO) any course (compulsory or not) can be chosen from our catalog.
Critically Reflecting on Intelligent Systems in Society (3 ECTS, compulsory for CAS & DAS)
In this course, students will learn how to critically reflect on the use of intelligent systems in society. This includes assessing the potential effects and formulating well-founded positions on ethical questions. Critical reflection is relevant for any application whether it is in engineering, simulations, aviation, education, data science, or any other area. The course will enable students to transfer their knowledge and implement it in their work. Moreover, they will be able to discuss issues and questions with others who might not think the way they do and open their mind to different perspectives.
Interdisciplinary AI Software Project (6 ECTS, compulsory for DAS)
The completion of the Interdisciplinary AI Software Project (6 ECTS) is mandatory for the Diploma of Advanced Studies (DAS) to round up the education in our biggest certificate. It can be completed either during the summer or winter term.
Module Description of the Interdisciplinary AI Software Project in C@mpus
How to use the course catalog?
In the following, we provide our course offerings.
- We provide module names and ECTS points. A short description of each course is given. More information can be found in C@mpus, including details on the lecture, prerequisites, and so forth.
- ST and WT denote summer term and winter term, respectively.
- DE (German) and EN (English) represent the language in which the lecture is given.
- The tag COMPULSORY highlights courses from which you have to choose a certain number for CAS and DAS (and which can also be chosen for MICRO)
Please refer to our FAQ before contacting us.
Work in progress...
...the course catalog is currently being reviewed and extended. Please check for updates regularly (as long as this notes remains).
AISA Course Catalog
- Modeling of Software-Intensive Systems (6 ECTS)
- This course introduces the foundational principles of modeling software-intensive systems, focusing on object-oriented modeling techniques. Key topics include structural and behavioral modeling using UML, formal software architecture modeling, and the modeling of digital twins. Participants will develop the skills to create precise and scalable models applicable to modern software and system architectures.
- Advanced Computing in Architecture
- Coming soon...
- Advanced Software Engineering (6 ECTS)
- Coming soon...
- AI Prototyping 101: From Idea to Reality (6 ECTS for AISA, 3 ECTS as FüSQ, ST, EN)
- The course "AI Prototyping 101: From Idea to Reality" introduces various creativity methods that empower students to tackle everyday challenges and even broader societal issues. Throughout the course, students will develop a prototype concept by applying these creativity techniques and using Artificial Intelligence (AI) tools to bring their ideas to life. In addition, students will learn effective pitching and presentation strategies to showcase their prototypes, gaining hands-on experience in communicating innovative ideas. The course introduces programming concepts and delves into AI's “black box” nature, offering insights into its underlying mechanisms. The course emphasizes teamwork, with students collaborating in groups composed of individuals from diverse disciplines. By the end of the course, participants will have the skills to conceptualize and create a prototype and the confidence to present and pitch their ideas. Requirements: no knowledge of programming or AI theory is necessary
- Basic Principles of Artificial Intelligence (6 ECTS, WT, DE, COMPULSORY)
- The course introduces the basics of artificial intelligence, starting from concepts of intelligence and agents, introducing different kinds of problems and games, and covering different methods and algorithms such as logic-based agents and probabilistic reasoning. The course enables students to classify AI problems and work on them using the methods and algorithms learned.
- Computing in Architecture (6 ECTS, EN, ST)
- This course introduces advanced computational methods like optimization and machine learning in the context of architectural design. Students will learn how to automate the search for good design candidates, how to analyze the resulting data, and how to make predictions from that data. The module focuses on performance-informed architectural design with building simulations, but students will be free to explore other applications of these methods as well.
- Data Processing for Engineers and Scientists (6 ECTS, EN, ST & WT)
- The course teaches basic knowledge of data acquisition, data preparation, data analysis, and data visualization, including elementary knowledge in image processing. Additionally, data-based/-assisted modeling is addressed. An extensive computer lab in Python accompanies the course. Additional material is available (templates, mini tutorials, learning module). The regular course takes place in the winter term. At the end of the summer term, an equivalent intensive course (2 weeks) is offered, as well.
- Einführung in Software Engineering (6 ECTS, ST, DE, COMPULSORY)
- Machine Learning (6 ECTS, ST, EN, COMPULSORY)
- In this course, students will acquire an in-depth understanding of Machine Learning methods. The concepts and formalisms of Machine Learning are understood as a generic approach to a variety of disciplines, including image processing, robotics, computational linguistics, and software engineering. This course will enable students to formalize problems from such disciplines in terms of probabilistic models, and derive respective learning and inference algorithms.
- Machine Perception and Learning
- Coming soon...
- Mathematics of Machine Learning
- Coming soon...
- Probabilistic Machine Learning (6 ECTS, EN, WT)
- The course introduces the basics of probabilistic machine learning (including methods of explainable AI, XAI). It covers algorithms and methods such as Bayes’ net, Variable elimination, Lime, SHAP Values, and counterfactuals. The course enables students to classify probabilistic machine learning and address problems using the methods and algorithms learned.
- Quantitative Evaluation of Software Designs (6 ECTS, EN, ST)
- This course teaches key methods of quantitative evaluation of software designs. Key topics include the quantitative analysis using UML2, an overview of analysis models including their statistical foundations and solvers, as well as methods for model checking. Participants will develop the skills to design and evaluate software according to quantitatively analyzable requirements like performance, reliability, safety, scalability, elasticity, costs, and other software qualities.
- Reinforcement Learning (6 ECTS, ST, EN, COMPULSORY)
- Reinforcement Learning considers how an agent, interacting with a world, can improve or learn optimal behavior based on their own experience or teacher demonstration. This branch of Artificial Intelligence and Machine Learning has become an increasingly important foundation of robust intelligent systems and robotics. This course will introduce the theory of Reinforcement Learning and then discuss state-of-the-art algorithms in this area. It will enable students to apply Reinforcement Learning algorithms in simulated domains and real robotic systems.
- Security and Privacy (6 ECTS, DE/EN, ST)
- Participants will gain an in-depth understanding of key topics in information security and privacy, focusing on advanced issues in the field. The topics covered may vary depending on current developments and the focus of the course. Potential topics include Secure Multi-Party Computation, Zero-Knowledge Protocols, cryptographic protocol verification, blockchains and smart contracts, differential privacy, and privacy-preserving data mining, as well as secure e-voting systems. Each of these areas addresses real-world challenges in maintaining security and privacy in modern digital environments.
- Simulation Software Engineering (6 ECTS, EN, WT)
- The course introduces the key concepts of research software engineering tools and their handling. The tools include continuous integration, virtualization, building & packaging, and version control. Moreover, the course provides an overview of important large-scale open-source simulation software packages. Ultimately, the participants learn how to contribute to such software packages and that knowing how to program is not enough to develop sustainable and reusable research software.
- System and Web Security (6 ECTS, DE/EN, ST)
- Participants are made aware of common security vulnerabilities and attack vectors in computer systems and the web. They become familiar with specific attacks and the underlying principles, as well as common defense mechanisms. IT systems are continuously under attack from various types of adversaries, including criminal organizations, intelligence agencies, and industrial espionage by states and companies. This course covers the most prevalent attack vectors on computer systems, including mobile devices and the web. Topics include stack and heap overflows, format string vulnerabilities, integer overflows, return-oriented programming, Cross-Site Scripting (XSS), SQL Injections, and Cross-Site Request Forgery (XSRF). Additionally, the course discusses common defense mechanisms, such as access control, address space layout randomization (ASLR), static code analysis, security monitoring, input/output sanitization, and prepared statements.