Curriculum
Head of Studies
Per Bækgaard Associate Professor Phone: +45 45253908 Mobile: +45 93510543 pgba@dtu.dk
Programme provision
To obtain the MSc degree in Human-Centered Artificial Intelligence, the student must fulfil the following requirements:
- Have passed General Competence Courses adding up to at least 30 ECTS points
- Have passed Technological Specialization Courses adding up to at least 30 ECTS points
- Have performed a Master Thesis of at least 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 points of the entire study up to 120
Curriculum
Mandatory innovation courses
The mandatory course below combine technological aspects with innovation.
Students must pick one of the following (equivalent) courses:
| 42500 | Innovation in Engineering | 5 | point | January |
| or | ||||
| 42504 | Innovation in Engineering | 5 | point | August |
| or | ||||
| 42501 | Innovation in Engineering | 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 |
| or | ||||
| 42505 | Facilitating Innovation in Multidisciplinary teams | 5 | point | August |
| or | ||||
| 42503 | Facilitating Innovation in Multidisciplinary teams | 5 | point | June |
Mandatory Human-Centered and Digital Innovation course
The mandatory course below introduces a human-centered design approach, combined with aspects of digital innovation, and are part of the DTU Compute Digital Innovation Canon.
Students must pick the following course:
| 02809 | UX Design Prototyping | 5 | point | Autumn E1A (Mon 8-12) |
Mandatory Machine Learning Course
The mandatory course below introduces essential and required aspects of machine learning and data mining.
Students must pick the following course:
| 02450 | Introduction to Machine Learning and Data Mining | 5 | point | Spring F4A (Tues 13-17), Autumn E4A (Tues 13-17) |
Other general competence courses
Students must choose additionally at least 15 points among the courses listed in the two subgroups below; at least 10 ECTS must come from the first subgroup:
| 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) |
Students that pick courses from the subgroup below will be credited 5 ECTS in the "other general competence" category and any additional points will count as electives. Thus, for students that pick 1) 38103 X-Tech Entrepreneurship, which is a 10 ECTS course, and/or 2) multiple of the courses below, 5 ECTS counts toward the "other general competence" category and additional points will count as electives.
| 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) |
| 38108 | Technology and Innovation Management | 5 | point | Autumn E3B (Fri 13-17) |
Choose at least 30 points among the following:
| 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 E1A (Mon 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) |
| 02504 | Computer Vision | 5 | point | Spring F3B (Fri 13-17) |
| 02506 | Advanced Image Analysis | 5 | point | Spring F5B (Wed 13-17) |
| 02507 | Project work within Image Analysis and Computer Graphics | 5 | point | January |
| 02514 | Deep Learning in Computer Vision | 5 | point | June |
| 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) |
| 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 |
| 42081 | Staging co-creation and creativity | 5 | point | Autumn E1B (Thurs 13-17) |
Note: The course 02460 will not be offered in the 2022/2023 academic year. Students are encouraged to pick courses 02456 Deep learning and/or 02471 Machine learning for signal processing instead. Students that have had these courses prior to enrollment are welcome to discuss their study plan options with the Head of Studies.