Prerequisite knowledge and examination requirements for the selected course offerings.
Each Fach combines the 26S and 26W course lists supplied from AAU Campus. Open a course to see the expected background, what must be completed, and the important grading thresholds.
Live catalogue note. AAU Campus indicates that the 26W teaching offer may still be expanded or changed before the semester begins. This page reflects the course pages checked on 6 September 2026.
Select one or more flags. Courses must match all selected flags.
Fach key 7599 · 8 listed offerings
Basic knowledge of modern Web technologies. Logic & Logic Programming and Databases are recommended, but not mandatory.
Written exam covering all lecture topics plus homework. At least 50% of the exam points and 75% of the homework must be achieved. AI use must be disclosed, and students must be able to answer questions about submitted solutions.
Introductory courses in Artificial Intelligence.
Presentations, feedback, reviews and a final paper. The quality of the presentation, paper and written contributions is assessed.
No explicit prerequisite is stated.
Written exam. An optional student project and contributions to lecture discussions can add bonus points. Topics include reinforcement learning, learning in logic, qualitative reasoning and learning from noisy data.
Basic AI concepts, particularly knowledge representation and reasoning.
Two or three implementation projects. Assessment focuses on implementation performance and the comprehensiveness of the documentation.
Solid software-engineering knowledge: development methodologies, requirements engineering, OOP, databases, version control, Python or JavaScript/TypeScript, testing, code quality and metrics. Required setup: Python or Node.js, an Internet-capable device and an active AI coding assistant.
Theoretical mini-test and practical in-class lab work, weighted 50/50. Both parts must reach at least 30 points. The grading scale is 90+ = 1, 80–89 = 2, 70–79 = 3, 60–69 = 4, below 60 = 5.
No explicit prerequisite is currently published.
No examination method, content or grading criteria are currently published on the course page.
No explicit prerequisite is stated.
Two assessments and a mini-project. All deliverables must be submitted; normally at least 50% overall and at least 50% in each assessment are required.
Basic probability theory, linear algebra and optimization methods. Python is advantageous.
Design and implementation of a deep-learning project plus practical exercises. AI use must be disclosed, and students must answer questions about their code, methods and literature during the defensio.
Fach key 7600 · 3 listed offerings
Basic programming skills.
Small software projects during the semester and a final written exam. Project and presentation quality are assessed.
Database technologies and the ability to install tools and systems on your computer.
Active participation 20%, quality of assignment solutions 30%, written exam 50%.
Completed Bachelor’s studies in computer science/informatics or a related field.
Participation, assignments, seminar paper, oral presentation and presentation material. Timely delivery, quality, completeness and correctness are required. AI is limited to spelling/syntax support and must be disclosed.
Fach key 7601 · 6 listed offerings
Database technology and knowledge engineering; writing lab informatics is highly recommended.
Extended abstract 15%, seminar paper 40%, presentation 15%, reviews 20%, discussion participation 10%.
Databases and object-oriented programming.
Active participation and presentations 40%; final exam 60%.
Basic programming skills.
Small software projects during the semester and a final written exam. Project and presentation quality are assessed.
No explicit prerequisite is stated.
Written final exam covering lectures and assignments; at least 60% of the total points is required.
No explicit prerequisite is stated on the page.
Weekly assignments and active participation; written closed-book exam. Overall grade: uploaded solutions, presentation and discussion 40%, final exam 60%.
Database technologies and the ability to install tools and systems on your computer.
Active participation 20%, quality of assignment solutions 30%, written exam 50%.
Fach key 7602 · 4 listed offerings
No explicit prerequisite is stated.
Presentation 50%; projects and assignments 50%.
Basic computer-systems and programming concepts. Distributed systems, cloud computing and performance evaluation are welcome.
Participation and class activities 10%, quizzes 20%, assignments 30%, projects 40%.
Basic computer-systems and programming concepts. Distributed systems, cloud computing and performance evaluation are welcome.
Participation and class activities 10%, quizzes 20%, assignments 30%, projects 40%.
Computer organization, operating systems and computer networks.
Seminar paper, presentation and discussion contributions. Generative AI is not permitted throughout the reviews and seminar-paper writing process.
Fach key 7603 · 4 listed offerings
No explicit prerequisite is stated.
Discussions, assignments and a digital closed-book exam. The grade is based on participation, assignments, project contributions and the exam. AI is limited to spelling/syntax checking for written assignments.
Bachelor-level courses in Interactive Systems.
Assignments, prototypes and user-centred evaluations. Attendance, active participation and quality of work matter. AI use must be limited and documented.
Completed Bachelor’s studies in computer science/informatics or a related field.
Participation, assignments, seminar paper, oral presentation and presentation material. Timely delivery, quality, completeness and correctness are required. AI is limited to spelling/syntax support and must be disclosed.
Basics in Human-Computer Interaction.
Group work, presentations and prototype development. Active participation, assignment quality, prototype quality and correct use of user-centred methods are required. Undisclosed AI use can lead to exclusion.
Fach key 7604 · 6 listed offerings
Basic understanding of System Security.
Presentations and two final reports. Both the risk-management and security-management sections must be completed positively.
Profound knowledge of ML/AI models and architectures, their training and data curation, plus adversarial thinking and cybersecurity fundamentals.
Written exam 50%, project presentation 25%, practical demonstration 25%. Attendance is required, with no more than three absences. A functional technical demonstration is mandatory.
Basic knowledge of system security.
Student talk and seminar thesis. At least 50% must be achieved separately in both the talk and the written paper.
No explicit prerequisite is stated.
Written final exam covering lectures and assignments; at least 60% of the total points is required.
No explicit prerequisite is stated.
Moodle quizzes and coursework. At least 50 points overall are required to pass.
No prerequisite is currently published.
No examination method, content or grading criteria are currently published on the course page.
Fach key 7605 · 5 listed offerings
Computer organization, operating systems and computer networks.
Seminar paper, presentation and discussion contributions. AI use is allowed only to a limited extent and must be disclosed.
No explicit prerequisite is stated.
Implementation assignments covering lecture topics and examples. At least 50% is required for a passing grade. AI-generated code or text must be disclosed.
Operating systems, computer networks/network programming and introductory multimedia or distributed multimedia.
Presentations, demonstrations and a final meeting. Active participation and submission of all presentations/demonstrations are required.
Basic computer-systems and programming concepts. Distributed systems, cloud computing and performance evaluation are welcome.
Participation and class activities 10%, quizzes 20%, assignments 30%, projects 40%.
Good programming, operating systems and computer networks. Multimedia coding is advantageous but not mandatory. AAU students are expected to have completed Operating Systems, Computer Networks and Introduction to Multimedia Technology.
Presentation 50%; projects and assignments 50%.
Fach key 7606 · 5 listed offerings
No explicit prerequisite is stated.
Presentation, discussion/opposition and written review of a scientific paper. AI may improve wording, but may not evaluate papers or generate reviews.
Basic machine learning and good Python programming.
One lab assignment, student presentation and written report. Quality of the solution, presentation and report is assessed. AI use must be disclosed.
No explicit prerequisite is stated.
Written final exam covering lectures and assignments; at least 60% of the total points is required.
No explicit prerequisite is stated.
Two lab reports and presentations at 30% each, plus a final online exam at 40%.
Good programming in any language and basic software-testing knowledge.
Exercises and written exam. Both components must exceed 50% for a passing result.