Do you want to contribute to the current transformation of our digital society as an artificial intelligence specialist? The Master’s programme in Artificial Intelligence gives broad knowledge in AI and deepened knowledge in profile areas such as theoretical foundations of artificial intelligence, human-AI interaction, intelligent robotics, machine learning or data science. Following your degree you can pursue a research career or a career as an AI specialist in industry or the public sector.
The Master’s programme in Artificial Intelligence gives broad knowledge in artificial intelligence and deepened knowledge in one of five profile areas of special interest. The profile areas are: theoretical foundations of artificial intelligence, human-AI interaction, intelligent robotics, machine learning, and data science.
Necessary prerequisites for admission to the programme are theoretical knowledge and practical skills regarding algorithmic problem solving, including well-developed programming skills. This is typically acquired through studies in computer science. In addition, prerequisites include courses in mathematics such as numerical analysis, linear algebra and a course in either logics or statistics.
The programme contains four mandatory AI courses common for all profiles, to be attended during the first year: on the foundation of AI, on AI and its methods and applications, on machine learning, and on designing interactive intelligent systems. In the profile area data science there are four additional mandatory courses that you require to receive a degree in Mathematical Statistics. For the four remaining areas, leading to a degree in Computing Science with a profile in Artificial Intelligence, you have a higher freedom to choose courses depending on interest, although some courses are strongly recommended.
The courses on the programme consist of lectures, seminars, group work, and tutorials in conjunction with different types of assignments and laboratory work. These assignments are usually mandatory and often consist of software development of some kind. In the courses included in the profile areas relating to human-AI interaction, the assignments typically consist of a student project that is conducted in collaboration with a societal organization addressing a societal challenge. In these projects students are expected to collaborate in interdisciplinary teams and with representatives from a societal organisation. Organisations include both industry and public organisations.
Count on a 40-hour work week even if there are fewer hours scheduled. On master level you are expected to take full responsibility for organising your study work tasks so that deadlines are met, and so that collaborative work within student projects are manageable within office hours.
Your teachers are also scientists in the fields in which they teach. All teaching takes place in English.
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The PDF form is available for download here:
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Foundations of Logic and Model Theory or Statistics for Engineers
Fundamentals of Artificial Intelligence
Artificial Intelligence - Methods and Applications
Profile areas in Computing Science:
• Reasoning and decision making
• Machine Learning
• Human-AI Interaction
• Intelligent Robotics
Profile areas in Mathematical Statistics:
• Data Science
Basic courses in Computing Science:
If you aim for one of the profile areas in Computing Science you will get a degree in Computing Science with a profile in AI and will also have to take these two mandatory courses:
Design of Interactive Intelligent Systems
Thesis project for Degree of Master of Science in Computing Science (specialisation in Artificial Intelligence)
Basic courses in Mathematical Statistics:
If you aim to follow the Data Science profile you will get a degree in Mathematical Statistics and will have to take these five mandatory courses:
Stochastic Processes and Simulation
Design of Experiments and Advanced Statistical Modelling
Multivariate Data Analysis
Big Data and high-dimensional data analysis
Thesis Project for the Degree of Master of Science in Mathematical Statistics
Artificial intelligence is embedded in our digital tools to make use of the vast amount of data that is collected, for giving additional value tailored to individuals and situations, and for building digital infrastructures for society. Our digital society is rapidly transforming in ways that affect how we work, educate and entertain ourselves, socialize and engage in the society. As a consequence, society is facing a rapidly increasing demand for the competence in artificial intelligence that is necessary to push the development in ways that are beneficial to the society. Industry’s and public organisations’ demand for expertise in artificial intelligence will increase even more in the foreseeable future.
With the broad and core competence in artificial intelligence that the program will give, your future areas of work will mainly depend on your own interest areas. Work tasks can range from developing the future digital tools for improving the environment, health, education of children, to tools for addressing societal issues such as democracy, justice, safety, or building infrastructures, software for self-driving cars and other transportation systems. You may develop different types of decision support and business intelligence, AI architectures, data management strategies and responsible AI.
Examples of job titles:
• AI Architect
• AI Product Manager
• AI Technology Software Engineer
• Data Scientist
• AI Interaction Designer
• AI Ethicist
• Doctoral Student
• Research Engineer