Master's Programme in Information and Communication Technology
Artificial Intelligence, 5-year master programme
Language of instruction
On successful completion of this course, the student should
be able to design, analyze, and implement advanced systems, or solve an advanced problem.
have comprehensive knowledge and the ability to work out solutions within the sub area the student chooses to specialize in.
be able to identify relevant literature and apply theoretical models to the problems at hand.
The course is based upon ongoing research in the department or relevant needs of the industry, and deepens expertise within a focused application- or research area. Individually or in small groups, students specialize in topics that are approved by members of the academic staff. The topics should be relevant for the specialization profile the students have chosen. The students may be required to present scientific papers.
Pre-approved course topics: - Certifications - eHealth - Reinforcement learning - Embedded Systems - Mobile Radio Communication - 5G and IoT: Advanced
Be aware that all topics in the seminar courses might not be available every semester.
In addition to the pre-approved course topics, it is possible to propose a certain topic that a student can work on from research groups at UiA or from industry. The course responsible person must approve the topic based on two requirements: (1) The topic should be within the ICT domain and the technical depth of the topic is at Master level. (2) There is an employee at UiA with at least a Master's degree in the relevant field who is the supervisor of the topic.
Combination of lectures, assignments, paper studies, lab, report writing and self-study. The tasks are done individually or in small groups with group supervision.
The work load for the average student is approximately 200 hours.
Assessment methods and criteria
Graded portfolio assessment, individually or in groups. Groups are given joint grades. Information about the content of the portfolio will be given in Canvas by the start of the semester.
The study programme manager, in consultation with the student representative, decides the method of evaluation and whether the courses will have a midterm- or end of term evaluation, see also the Quality System, section 4.1. Information about evaluation method for the course will be posted on Canvas.