Machine Learning at Scale - Specialization
Specialisation: Machine Learning at Scale
"Machine Learning at Scale" focuses on efficiently designing and implementing machine learning algorithms and systems and on methods for analysing data.
To fulfill the requirements for the specialisation, the student must follow the requirements in the general curriculum for the programme such that at least 35 ECTS points are obtained among the recommended courses below.
Note that specialisations are merely recommended ways of choosing the courses in the curriculum. Students are not admitted to a specialisation but to the programme and it is possible to choose among all the courses in the curriculum following the requirerements in the general curriculum. However, if a specialisation has been fulfilled, the title of the specialisation may be added to the diploma on request.
Recommended courses
Choose at least 35 ECTS among the following courses:
| 02282 | Algorithms for Massive Data Sets | 7.5 | point | Spring F1A (Mon 8-12) |
| 02289 | Algorithmic Techniques for Modern Data Models | 5 | point | Autumn E4B (Fri 8-12) |
| 02456 | Deep learning | 5 | point | Autumn E2A (Mon 13-17) |
| 02460 | Advanced Machine Learning | 5 | point | Spring F1B (Thurs 13-17) |
| 02471 | Machine learning for signal processing | 5 | point | Autumn E1B (Thurs 13-17) |
| 02476 | Machine Learning Operations | 5 | point | January |
| 02477 | Bayesian machine learning | 5 | point | Spring F2A (Mon 13-17) |
| 02582 | Computational Data Analysis | 5 | point | Spring F2B (Thurs 8-12) |
| 02614 | High-Performance Computing | 5 | point | January |
| 02830 | Advanced Project in Digital Media Engineering | 10 | point | Autumn E5B (Wed 13-17) |
Addititional relevant courses
Although not part of the requirements for the specialisation, the following courses may also be relevant for the student:
| 02249 | Computationally Hard Problems | 7.5 | point | Autumn E3A (Tues 8-12) |
| 02409 | Multivariate Statistics | 5 | point | Autumn E1A (Mon 8-12) |
| 02612 | Constrained Optimization | 5 | point | Spring F4A (Tues 13-17) |