A candidate who has completed his or her qualification should have the following learning outcomes defined in terms of knowledge, skills and general competence:
The overall learning outcome of this master, common for all specialisations, is the following:
- K1 (common) - Has advanced knowledge in informatics and advanced theoretical, methodological and technical knowledge within the chosen specialisation.
- K2 (common) - Has basic knowledge in research methods used in informatics in general and deep knowledge of the methods used within the chosen specialisation.
- K3 (common) - Can analyse and solve problems using general methods in informatics.
The learning outcomes for each specialization are as follows:
Knowledge for Databases and search (DS)
- K1 (DS) – Has advanced knowledge about systems and technologies for processing, storage and management of information, their application and characteristics.
- K2 (DS) – Has advanced knowledge about technologies, methods and techniques for indexing, querying and searching structured data and unstructured media, like text.
- K3 (DS) – Has advanced knowledge about identification, description and classification of information, with focus on selected standards, systems and information quality.
Knowledge for Artificial intelligence (AI)
- K1 (AI) – Has fundamental knowledge about how a problem can be represented as a search space and solved.
- K2 (AI) – Has deep knowledge of knowledge representation techniques and artificial intelligence (AI) methods for analysis and reasoning, and how they can be combined with classic methods and techniques, e.g. based on probability theory.
- K3 (AI) – Has fundamental knowledge about how the human brain works and AI methods based on this knowledge.
Knowledge for Software (SW)
- K1 (SW) – Has advanced knowledge about technology and tools for realising large software systems (make the system right).
- K2 (SW) – Has advanced knowledge about methods for modelling, development, quality assurance and governance of large software systems.
Knowledge for Interaction design, game and learning technology (ID)
- K1 (ID) – Has advanced knowledge of methods for involving users in the design process.
- K2 (ID) - Has advanced knowledge of methods for design, prototyping and evaluation of user interfaces, games and learning technology.
- K3 (ID) – Has exensive knowledge of the interaction designer’s role in large IT projects.
The overall learning outcome of this master, common for all specialisations, is the following:
- S1 (common) - Can effectively and effeciently develop and evaluate IT systems and solutions within the chosen specialisation.
- S2 (common) - Can analyse and assess IT systems and solutions according to technical and non-technical factors.
- S3 (common) - Can use knowledge and skills on new problems and work independently with research and development within the field of informatics.
The learning outcomes for each specialization are as follows:
Skills for Databases and search (DS)
- F1 (DS) – Can specify, design, implement and evaluate systems for storing, updating, indexing, search and analysis of structured data, text and other media types.
Skills for Artificial intelligence (AI)
- F1 (AI) – Can realise systems using AI methods in combination with classic techniques, based on each method’s strengths and weaknesses.
Skills for Software (SW)
- F1 (SW) – Can identify, specify and analyse needs and requirements, to realise an appropriate software system (make the right system).
- F2 (SW) – Can realise and govern a software system effectively and efficiently.
Skills for Interaction design, game and learning technology (ID)
- F1 (ID) - Can identify, define and analyse various customer and user needs.
- F2 (ID) – Can work effectively and efficiently with tools for design, prototyping and evaluation of user interfaces, game and learning technology.
- F3 (ID) – Can work effectively and efficiently in user-oriented IT projects with requirements, design, implementation and testing.
The overall learning outcome of this master, common for all specialisations, is the following:
- G1 (common) - Can communicate effectively and efficiently about informatics isses, both with informatics specialists and non-specialists.
- G2 (common) – Can collaborate across disciplines and contribute effectively in multi-disciplinary innovation processes.
- G3 (common) – Can reflect on the role of information technology in society and related societal, ethical and legal issues.
- G4 (common) – Can «learn» new methods and technologies within informatics and has a solid foundation for life-long learning.
The learning outcomes for each specialization are as follow
General competence for Databases and search (DS)
- G1 (DS) – Has special understanding of governance of data at large scale and over long time.
General competence for Artificial intelligence (AI)
- G1 (AI) – Has special understanding of how AI techniques can be utilized in an information system, and the potential and concequences such usage may have.
General competence for Software (SW)
- G1 (SW) – Has special understanding of possibilities and concequences of digitalisation.
General competence for Interaction design, game and learning technology (ID)
- G1 (ID) – Has special understanding of how to ensure adequate usability of systems.
