Curriculum for Human-Centered Artificial Intelligence
Programme provision
To obtain the MSc degree in Human-Centered Artificial Intelligence, the student must fulfil the following requirements:
- Have passed Polytechnical foundation courses adding up to at least 10 ECTS
- Have passed Programme-specific courses adding up to at least 50 ECTS
- Have performed a Master Thesis of 30 ECTS points within the field of the general program
- Have passed a sufficient number of Elective courses to bring the total number of ECTS of the entire study to 120 ECTS
Curriculum
Polytechnical foundation courses (10 ECTS)
The following courses are mandatory:
| 12100 | Quantitative Sustainability (Polytechnical Foundation) | 5 | point | F7 (Tues 18-22) |
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| 12106 | Quantitative Sustainability (Polytechnical Foundation) | 5 | point | Autumn E3B (Fri 13-17) |
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| 12105 | Quantitative Sustainability (Polytechnical Foundation) | 5 | point | E7 (Tues 18-22) |
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| 12101 | Quantitative Sustainability (Polytechnical Foundation) | 5 | point | Spring F3B (Fri 13-17) |
| 42500 | Innovation in Engineering (Polytechnical Foundation) | 5 | point | January |
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| 42504 | Innovation in Engineering (Polytechnical Foundation) | 5 | point | August |
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| 42501 | Innovation in Engineering (Polytechnical Foundation) | 5 | point | June |
Students with advanced innovation competences should take 42502/42503/42505 Facilitating Innovation in Multidisciplinary teams as an alternative to 42500/42501/42504 Innovation in Engineering.
| 42502 | Facilitating Innovation in Multidisciplinary Teams | 5 | point | January |
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| 42505 | Facilitating Innovation in Multidisciplinary Teams | 5 | point | August |
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| 42503 | Facilitating Innovation in Multidisciplinary Teams | 5 | point | June |
Programme specific courses (50 ECTS)
Innovation course II - mandatory (5 ECTS):
| 02809 | UX Design Prototyping | 5 | point | Autumn E1A (Mon 8-12) |
Core competence course - mandatory (5 ECTS)
| 02450 | Introduction to Machine Learning and Data Mining | 5 | point | Spring F4A (Tues 13-17), Autumn E4A (Tues 13-17) |
Core competence courses - choose additionally 10 ECTS among the following courses:
| 02282 | Algorithms for Massive Data Sets | 7.5 | point | Spring F1A (Mon 8-12) |
| 02504 | Computer Vision | 5 | point | Spring F3B (Fri 13-17) |
| 02561 | Computer Graphics | 5 | point | Autumn E5A (Wed 8-12) |
| 02582 | Computational Data Analysis | 5 | point | Spring F2B (Thurs 8-12) |
| 02805 | Social graphs and interactions | 10 | point | Autumn E5 (Wed 8-17) |
| 02806 | Social data analysis and visualization | 5 | point | Spring F3A (Tues 8-12) |
| 02807 | Computational Tools for Data Science | 5 | point | E7 (Tues 18-22) |
| 02180 | Introduction to Artificial Intelligence | 5 | point | Spring F3A (Tues 8-12) |
| 02238 | Biometric Systems | 5 | point | June |
| 02266 | User Experience Engineering | 5 | point | January |
| 02282 | Algorithms for Massive Data Sets | 7.5 | point | Spring F1A (Mon 8-12) |
| 02285 | Artificial Intelligence and Multi-Agent Systems | 7.5 | point | Spring F4A (Tues 13-17) |
| 02289 | Algorithmic Techniques for Modern Data Models | 5 | point | Autumn E4B (Fri 8-12) |
| 02409 | Multivariate Statistics | 5 | point | Autumn E1A (Mon 8-12) |
| 02417 | Time Series Analysis | 5 | point | Spring F4B (Fri 8-12) |
| 02443 | Stochastic Simulation | 5 | point | June |
| 02455 | Experiment in Cognitive Science | 5 | point | Autumn E5A (Wed 8-12) |
| 02456 | Deep learning | 5 | point | Autumn E2A (Mon 13-17) |
| 02458 | Cognitive Modelling | 5 | point | Autumn E2B (Thurs 8-12) |
| 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) |
| 02501 | Advanced Deep Learning in Computer Vision | 5 | point | Spring F4A (Tues 13-17) |
| 02504 | Computer Vision | 5 | point | Spring F3B (Fri 13-17) |
| 02506 | Advanced Image Analysis | 5 | point | Spring F5B (Wed 13-17) |
| 02516 | Introduction to Deep Learning in Computer Vision | 5 | point | Autumn E5B (Wed 13-17) |
| 02517 | Responsible AI: Algorithmic fairness and explainability | 5 | point | Autumn E2B (Thurs 8-12) |
| 02561 | Computer Graphics | 5 | point | Autumn E5A (Wed 8-12) |
| 02562 | Rendering - Introduction | 5 | point | Autumn E5B (Wed 13-17) |
| 02563 | Generative Methods for Computer Graphics | 5 | point | Spring F1B (Thurs 13-17) |
| 02566 | Creating Digital Visual Experiences | 10 | point | Spring F2 (Mon 13-17, Thurs 8-12) |
| 02580 | Geometric Data Analysis and Processing | 5 | point | Spring F5B (Wed 13-17) |
| 02582 | Computational Data Analysis | 5 | point | Spring F2B (Thurs 8-12) |
| 02613 | Python and High-Performance Computing | 5 | point | Spring F5A (Wed 8-12) |
| 02614 | High-Performance Computing | 5 | point | January |
| 02805 | Social graphs and interactions | 10 | point | Autumn E5 (Wed 8-17) |
| 02806 | Social data analysis and visualization | 5 | point | Spring F3A (Tues 8-12) |
| 02807 | Computational Tools for Data Science | 5 | point | E7 (Tues 18-22) |
| 02808 | Personal Data Interaction for Mobile and Wearables | 10 | point | Spring F5 (Wed 8-17) |
| 02830 | Advanced Project in Digital Media Engineering | 10 | point | Autumn E5B (Wed 13-17) |
| 02840 | Computer Game Programming Fundamentals (DADIU) | 15 | point | Autumn |
| 02841 | Computer Game Programming in a Production (DADIU) | 15 | point | Autumn |
| 38110 | Staging co-creation and creativity | 5 | point | Autumn E1B (Thurs 13-17) |
At most 5 ECTS from the following list can also be counted as programme specific courses
| 38102 | Technology Entrepreneurship | 5 | point | Autumn E1B (Thurs 13-17) |
| 38103 | X-Tech Entrepreneurship | 10 | point | Spring F3 (Tues 8-12, Fri 13-17), Autumn E3 (Tues 8-12, Fri 13-17) |
Head of Studies
Per Bækgaard Associate Professor Phone: +45 45253908 Mobile: +45 93510543 pgba@dtu.dk