Programme information
The XtAI course offers a variety of modules on AI, machine learning and 3D interfaces, in which both the theoretical basics and current application scenarios of state-of-the-art AI and XR methods are taught. The course is divided into mandatory and elective area, followed by thesis and thesis defence, with students needing to achieve a total of 120 ECTS credits for the course completion. Each module provides a specied number of ECTS credits upon successful completion. Students are free to choose modules from the elective area, so that modules of interest can be attended. Students must achieve 60 ECTS credits in total in the elective area through the selected modules. The Master's programme XtAI has a standard period of study of 4 semesters.
The module distribution required to complete the XtAI course, as well as detailed information on the available modules in each area are listed below.
We have also compiled a few suggestions on how a full Master's course may be constructed from these lectures under course schedules.
| Area | ECTS | |
|---|---|---|
| Mandatory courses | 35 | |
| AI&XR Labs | 25 | |
| Introduction in AI | 5 | |
| Machine Learning | 5 | |
| Mandatory Electives | 55 | |
| AI&XR Seminars | 5-10 | |
| Core AI Methods | 10-35 | |
| Core XR Methods | 10-20 | |
| AI&XR Applications & Technologies | 10-25 | |
| Abschlussbereich | 30 | |
| Thesis and Defense | 25+5 | |
| total | 120 |
In the elective area, students are able to choose their lectures from several sub-areas. For each sub-area, a minimum number of ECTS credits is required to obtain the degree. Additionally, students may only aquire a certain amount of ECTS credits from each sub-area.
Control Examination (KOP)
The control examination (KOP) is a check introduced in the new AI&XR programme version. In your first semester you must pass at least either the mandatory Introduction to AI or the Machine Learning course or you are considered to have failed the programme once. You can try again in your second semester, after that you will be dis-enroled from the programme.
In total you have six attempts (for each of the two courses: main exam at the end of the lecture period in the first semester, re-exam at the start of the lecture period in the second semester and an additional exam at the end of the lecture period in the second semester) to pass the control examination.
| This module contains projects, cooperations and talks on interesting topics: | The minimum number of ECTS credits to be achieved is 30. | |
|---|---|---|
| Module | ECTS credits | |
| Introduction in AI | 5 | Part of the KOP |
| Machine Learning | 5 | Part of the KOP (only in the xtAI programme version) |
| XtAI Lab 1 | 5 | |
| XtAI Lab 2 | 10 | |
| XtAI Lab 3 | 10 |
| Two seminars specifically geared towards eXtended Artificial Intelligence: | The minimum number of ECTS credits to be achieved is 5. In this sub-area a maximum of 10 ECTS may be achieved. |
|---|---|
| Module | ECTS credits |
| Seminar I | 5 |
| Seminar II | 5 |
| Indepth lectures on the core concepts of artificial intelligence | The minimum number of ECTS credits to be achieved is 10. In this sub-area a maximum of 35 ECTS may be achieved | |
|---|---|---|
| Module | ECTS credits | |
| Computer Vision | 5 | (only in the xtAI programme version) |
| Computer Vision 1 | 5 | (only in the AI&XR 2024 programme version) |
| Computer Vision 2 | 5 | (only in the AI&XR 2024 programme version) |
| Data Science 1 | 5 | |
| Data Science 2 | 5 | |
| Machine Learning 1 | 5 | (only in the xtAI programme version) |
| Machine Learning 2 | 5 | (only in the xtAI programme version) |
| Advanced Machine Learning | 5 | (only in the AI&XR 2024 programme version) |
| Natural Language Processing 1 | 5 | |
| Natural Language Processing 2 | 5 | |
| Selected Topics in AI Methods 1 | 5 | |
| Selected Topics in AI Methods 2 | 5 | |
| Theory of Artificial Intelligence 1 | 5 | |
| Theory of Artificial Intelligence 2 | 5 | |
| Machine Learning for Networks 1 | 5 | (only in the AI&XR 2024 programme version) |
| Machine Learning for Networks 2 | 5 | (only in the AI&XR 2024 programme version) |
| Image Processing and Computational Photography | 5 | (only in the AI&XR 2024 programme version) |
| Reinforcement Learning and Computational Decision Making | 5 | (only in the AI&XR 2024 programme version) |
| Multilingual NLP | 5 | (only in the AI&XR 2024 programme version) |
| Lectures on extended reality: | The minimum number of ECTS credits to be achieved is 10. In this sub-area a maximum of 20 ECTS may be achieved. |
|---|---|
| Module | ECTS credits |
| 3D User Interfaces | 5 |
| Multimodal Interfaces | 5 |
| Principles of Interactive Systems | 5 |
| Selected Topics in XR Methods | 5 |
| Lectures on applied Artiicial Intelligence: | The minimum number of ECTS credits to be achieved is 10. In this sub-area a maximum of 25 ECTS may be achieved. | |
|---|---|---|
| Module | ECTS credits | |
| 3D Point Cloud Processing | 5 | |
| Advanced Automation | 8 | (only in the xtAI programme version) |
| Autonomous Mobile Systems | 10 | (only in the AI&XR 2024 programme version) |
| Databases 2 | 5 | |
| Interactive Computer Graphics | 5 | |
| International Summer School XtAI | 5 | |
| Machine Learning in Bioinformatics | 5 | |
| Music Information Retrieval | 5 | |
| Robotics 1 | 5 | |
| Robotics 2 | 10 | |
| Scientific Internship | 10 | |
| Selected Topics in xtAI Application & Technologies | 5 | |
| Self-aware Computing | 5 | |
| Photogrammetic Machine Vision | 5 | (only in the AI&XR 2024 programme version) |
| Deep Reinforcement Learning for Optimal Control | 5 | (only in the AI&XR 2024 programme version) |
| Remote Sensing | 5 | (only in the AI&XR 2024 programme version) |
| Computer Science lectures aiding the use of Artifcial Intelligence | The minimum number of ECTS credits to be achieved is 0. In this sub- area a maximum of 10 ECTS may be achieved. | |
|---|---|---|
| Module | ECTS credits | |
| Deductive Databases | 5 | |
| Discrete Event Simulation | 5 | |
| Security of Software Systems | 5 | |
| Selected Topics in Computer Science | 5 | |
| Logic Programming | 5 | (only in the AI&XR 2024 programme version) |
| Systems Benchmarking | 5 | (only in the AI&XR 2024 programme version) |
| Advanced Programming | 5 | (only in the AI&XR 2024 programme version) |
| The minimum number of ECTS credits to be achieved is 30. | |
|---|---|
| ECTS credits | |
| Master’s Thesis XtAI | 25 |
| Oral Examination XtAI | 5 |
AI&XR (2024)
- Subject-specific provisons (FSB) and list of modules (SFB) (German; official publication on 31.1.2024): Detailed regulations on the degree program
- Overview of all module catalogues and subject-specific provisons provided by the examination office
- Qualification objectives (German): The qualification objectives describe what is to be achieved by the course and provide an orientation of what is expected in the course
- General academic and examination regulations (ASPO, 2015): The ASPO contain legally binding information for all Bachelor’s and Master’s degree programs at the University of Würzburg
xtAI (2020, 2023)
- Subject-specific provisons (FSB) and list of modules (SFB) (German; official publication on 31.1.2024): Detailed regulations on the degree program
- Overview of all module catalogues and subject-specific provisons provided by the examination office
- Qualification objectives (German): The qualification objectives describe what is to be achieved by the course and provide an orientation of what is expected in the course
- General academic and examination regulations (ASPO, 2015): The ASPO contain legally binding information for all Bachelor’s and Master’s degree programs at the University of Würzburg
