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 5 ECTS
  • Have passed Programme specific courses adding up to at least 55 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 (5 ECTS)

The following course is mandatory:

42500 Innovation in Engineering (Polytechnical Foundation) 5 point January
or
42504 Innovation in Engineering (Polytechnical Foundation) 5 point August
or
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
or
42505 Facilitating Innovation in Multidisciplinary Teams 5 point August
or
42503 Facilitating Innovation in Multidisciplinary Teams 5 point June

Programme specific courses (55 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)

Choose 35 ECTS among the rest of the programme specific courses: 

 

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)
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 January
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
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)
38108 Technology and Innovation Management 5 point Autumn E3B (Fri 13-17)

Elective Courses
Any course classified as MSc course in DTU's course base may be an elective course. This includes programme specific courses in excess of the minimal requirements. Master students may choose as much as 10 credit points among the bachelor courses at DTU and courses at an equivalent level from other higher institutions. In addition, it is possible to take MSc-level courses at other Danish universities or abroad.

Head of Studies

Per Bækgaard

Per Bækgaard Associate Professor Phone: +45 45253908 Mobile: +45 93510543

Programme Specification for Human-Centered Artificial Intelligence