Programme objectives

Master's Programme, Machine Learning, 120 credits (TMAIM), Programme syllabus for studies starting in autumn 2018

Last edit: 19/12/2018
Approved: 19/12/2018

Machine Learning is an area within Computer Science where computer systems are designed to learn from large sets of examples, similarly to the learning strategies of biological systems (like humans). Recently, Machine Learning has gained great importance for the design of search engines, robots, and sensor systems, and for the processing of large scientific data sets.

The focus of the Master’s programme in Machine Learning is on mathematical foundations and methods for Machine Learning. These applicationareas include topics such as computervision, speech communication, robotics, informationretrieval and/or computational biology.

In addition to this comes the Higher Education Ordinance goals for the degree.

Knowledge and understanding

A Master of Science in Machine Learning will be able to:

  • present a good knowledge of mathematical methods for Machine Learning, as well as how these are applied in in a number of application domains.
  • understand different Machine Learning problems deeply enough to select and apply suitable methods and computer tools to solve them,
  • formulate and approach new Machine Learning problem settings in a scientific manner; in a creative, critical and systematic way.

Skills and abilities

A Master of Science in Machine Learning will be able to:

  • work out solution strategies to different Machine Learning problems, knowing the capabilities and limitations of different methods and tools,
  • work efficiently in a teamwork environment in groups with people from different scientific and engineering background,
  • communicate with scientists and people active in engineering development in a competent manner both orally and in writing,
  • follow and participate in research and development related to the chosen track.

Ability to make judgments and adopt a standpoint

A Master of Science in Machine Learning will be able to:

  • critically judge a problem and in an independent manner acquire the information and knowledge that is necessary to establish a qualified opinion,
  • formulate and approach new Machine Learning problem settings in a scientific manner; in a creative, critical and systematic way,
  • identify the need for further knowledge in the field and take responsibility for keeping her/his personal knowledge up to date.

In addition to this the similar objectives for master degree defined in the Higher Education Ordinance (Högskoleförordningen) are applicable.