Each track includes four track specialization courses worth a total of 20 ECTS. The specialization courses bridge AI and ES and prepare for further research projects in the selected track.
The specialization courses aim to cover four themes, namely:
- Domain-specific knowledge
- AI in Engineered Systems
- Data Cultivation
- Learning and Intelligence
After consultation with your track mentor, you choose one course worth 5 ECTS for each theme. You can only select courses as listed in the specialization course list of the track you are registered.
Please be aware of the registration deadlines for enrolling in courses and examinations.
Courses at TU/e are scheduled in timeslots. Within your AI&ES study program you should prevent choosing core courses, specialisation courses and free elective courses that are scheduled in the same quartile and timeslot; you cannot follow two courses in the same quartile and timeslot.
Within your AI&ES study program you should also prevent choosing courses that overlap in schedules with the Interdisciplinary Team Project in Q3 and Q4. Use the quartiles and timeslots to build yourself a feasible schedule and study program.
Important updates about the specialization courses for 2022 student cohort
The students who have started their AI&ES master program in the 2022-2023 academic year, are allowed to choose from the new specialization courses that have been introduced for each track in the 2023-2024 academic year. For these courses the registration is done as usual, via Osiris. The track mentors are able to support the students with their choices for the new specialization courses. A list of the specialization courses from last year as published in the PER (OER) can be found in the Downloads section below.
Below is an overview of the specialization courses per track.
Track 1: High-tech systems and robotics
*Advanced sensing using deep learning will no longer be offered in 2023-2024; last examination year: 2023-2024.
Track 2: Mobility
| Available courses | Code | Theme(s) | Quarter | Timeslot |
|---|---|---|---|---|
| Advanced full-electric and hybrid powertrain design | 4AT030 | 1 | 4 | C |
| Vehicle control | 4AT080 | 2 | 4 | B |
| Decision making in transport and mobility | 1CM110 | 2 | 2 | A |
| Analysis and design of networked dynamical systems | 4DM70 | 2 | 4 | B |
| Computer vision and 3D image processing | 5LSH0 | 2, 3 | 2 | E |
| Physical and data-driven modelling | 4CM40 | 3 | 3 | D |
| System identification | 5SMB0 | 3 | 3 | C |
| Responsible data science | 2IX30 | 3 | 3 | C |
| *Advanced sensing using deep learning | 5AUA0 | 3, 4 | 4 | D1 |
| Automotive human factors | 0HM310 | 4 | 1 | C |
| Behavioral operations management | 1JM40 | 4 | 3 | A |
| Machine learning for multi-physics modeling and design | 4AI000 | 4 | 4 | E |
| Machine learning for systems and control | 5SC28 | 4 | 4 | B |
*Advanced sensing using deep learning will no longer be offered in 2023-2024; last examination year: 2023-2024.
Track 3: Healthcare
| Available courses | Code | Theme(s) | Quarter | Timeslot |
|---|---|---|---|---|
| Ultrasound in the (bio)medical engineering | 8VM60 | 1 | 2 | D |
| Orthopaedic soft tissues: biomechanics and mechanobiology | 8TM10 | 1 | 2 | D |
| Biomedical sensing technology | 5LSC0 | 2 | 3 | A2 & A3 |
| Monitoring of respiration and circulation | 5LSB0 | 2 | 2 | B1 |
| Behavioral operations management | 1JM40 | 2 | 3 | A |
| Human-robot interaction | 0HM280 | 2 | 4 | C |
| Brain-inspired optical computation | 5LTC0 | 2 | 4 | E2 & E3 |
| Computer vision and 3D image processing | 5LSH0 | 2, 3 | 2 | E |
| Medical image analysis | 8DC00 | 3 | 1 | E |
| Capita selecta in medical image analysis | 8DM20 | 3 | 3 | A & B1 |
| Image analysis for health-care technologies | 5LSJ0 | 3 | 3 | D1 |
| Video health monitoring | 5LIV0 | 3 | 2 | C2 |
| *Advanced sensing using deep learning | 5AUA0 | 3, 4 | 4 | D1 |
| Machine learning in medical imaging and biology | 8DM50 | 4 | 1 | B |
| Machine learning for signal processing | 5LSL0 | 4 | 4 | A2 & A3 |
| Convolutional neural networks for computer vision | 5LSM0 | 4 | 3 | E |
*Advanced sensing using deep learning will no longer be offered in 2023-2024; last examination year: 2023-2024.
Track 4: Smart cities
| Available courses | Code | Theme(s) | Quarter | Timeslot |
|---|---|---|---|---|
| Data science for intelligent buildings | 7LY5M0 | 1 | 1 | B |
| Decision making in transport and mobility | 1CM110 | 1 | 2 | A |
| Smart healthy urban environments | 7ZW5M0 | 1 | 2 | D |
| Building performance and energy systems simulation | 7LY3M0 | 1 | 1 | C |
| Digital design and manufacturing | 7KT4M0 | 2 | 2 | A |
| Advanced cognitive engineering | 0HM150 | 2 | 3 | E2 & E3 |
| Fundamentals of building information modeling | 7M900 | 3 | 2 | E |
| Algorithms for Geovisualization | 2IMA20 | 3 | 3 | E1 |
| Computer vision and 3D image processing | 5LSH0 | 3, 4 | 2 | E |
| *Advanced sensing using deep learning | 5AUA0 | 3, 4 | 4 | D1 |
| Convolutional neural networks for computer vision | 5LSM0 | 4 | 3 | E |
| Data fusion and semantic interpretation | 5XSK0 | 4 | 3 | E |
*Advanced sensing using deep learning will no longer be offered in 2023-2024; last examination year: 2023-2024.
Track 5: Science and Discovery
| Available courses | Code | Theme(s) | Quarter | Timeslot |
|---|---|---|---|---|
| Advanced fluid dynamics | 3MS010 | 1 | 1 | E |
| Chaos | 3MT100 | 1 | 3 | D |
| Soft matter physics | 3MS020 | 1 | 2 | B |
| Interfacial transport phenomena in engineering flows | 4BM60 | 1 | 1 | D2 & D3 |
| Microscale modeling of heat storage materials | 4SE20ONL | 1 | 2 | no timeslot |
| Heat and flow in microsystems | 4EM40 | 1 | 2 | C |
| Advanced computational continuum mechanics | 4MM10 | 1 | 2 | A |
| Scientific computing for Mechanical Engineering | 4EM30 | 1 | 3 | B |
| Computational and mathematical physics | 3MA010 | 2 | 1 | B |
| Optimal control and reinforcement learning | 4SC000 | 2 | 2 | D |
| Advanced computational fluids and plasma dynamics | 3MT120 | 2 | 3 | E |
| Physics modeling and simulations | 3FMX0 | 2 | 1 | E |
| Model reduction | 5LMA0 | 3 | 2 | C |
| Advanced simulation | 2DI66 | 3 | 3 | B |
| Research topics in data mining | 2AMM20 | 3 | 1 | B |
| Physical and data-driven modelling | 4CM40 | 3 | 1 | D |
| Machine learning for multi-physics modeling and design | 4AI000 | 4 | 4 | E |
| Machine learning for fluid mechanics | 3MT170 | 4 | 1 | D |
Track 6: Manufacturing Systems
| Available courses | Code | Theme(s) | Quarter | Timeslot |
|---|---|---|---|---|
| Manufacturing technology | 1CM160 | 1 | 1 | D |
| Modeling and analysis of manufacturing systems | 1CM10 | 2 | 2 | D |
| Modeling and control of manufacturing networks | 4DM40 | 2 | 4 | A |
| Integrated system design | 4CM70 | 2 | 2 | E |
| *Supervisory control | 4CM30 | 2 | 3 | D |
| Supervisory control of cyber physical systems | 4SC080 | 2 | 3 | D |
| Multi-echelon inventory management | 1CM100 | 2 | 3 | C1 |
| Advanced maintenance and service logistics | 1CM120 | 2 | 2 | A |
| Advanced simulation | 2DI66 | 3 | 3 | B |
| Data-driven artificial intelligence | 1BM110 | 3 | 3 | C2 |
| Optimal control and reinforcement learning | 4SC000 | 4 | 2 | D |
| Human-robot interaction | 0HM280 | 4 | 4 | C |
| Behavioral operations management | 1JM40 | 4 | 3 | A |
| Artificial intelligence for logistics and its interfaces | 1CM240 | 4 | 3 | D1 |
*Supervisory control will no longer be offered in 2023-2024. The course will be replaced by Supervisory control of cyber physical systems (4SC080).