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 methods to assess sustainability (Polytechnical Foundation) | 5 | point | F7 (Tues 18-22) |
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| 12106 | Quantitative methods to assess sustainability (Polytechnical Foundation) | 5 | point | Autumn E3B (Fri 13-17) |
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| 12105 | Quantitative methods to assess sustainability (Polytechnical Foundation) | 5 | point | E7 (Tues 18-22) |
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| 12101 | Quantitative methods to assess 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 (mandatory)
Innovation course II - mandatory (5 ECTS):
| 02810 | UX Design Prototyping | 5 | point | Autumn E1A (Mon 8-12) |
Note: Students that previously had the course 02809 do not need to take the course 02810, but must instead choose an additional course among the advanced program specific courses listed below.
Core competence program specific course (mandatory)
Machine Learning - Mandatory (5 ECTS)
| 02452 | Machine Learning | 5 | point | Autumn E4A (Tues 13-17) |
Note: Students that previously had either of the courses 02450 or 02451 do not need to take the course 02452, but must instead choose an additional course among the advanced program specific courses listed below.
Core competence program specific courses (additional)
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 E5B (Wed 13-17) |
| 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 | Autumn E5B (Wed 13-17) |
| 02566 | Creating Digital Visual Experiences | 10 | point | Spring F2 (Mon 13-17, Thurs 8-12) |
| 02581 | Geometric Data Analysis and Processing | 5 | point | Autumn E1B (Thurs 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