Artificial Intelligence is a field that studies synthesis and analysis of digital agents. A digital agent is a program that have the skills to act intelligent, even if it is in a very limited capacity. Some central goals for Artificial Intelligence are:
In Artificial Intelligence we study topics as learning, knowledge representation and reasoning, multi-agent systems, search algorithms, planning, natural language processing, robotics, and perception.
Learning in Artificial Intelligence is about how we can improve behavior in a digital agent over time, and how we extract new knowledge from available data.
Knowledge representation in Artificial Intelligence is about how information that is understandable for humans as text, pictures, sounds etc... can be represented such that a machine can understand it. For example, like logic, binary code, a programming language etc... Automatic reasoning is about how we can build algorithms that solves problems and perform decisions utilizing information and knowledge represented in a machine-understandable way.
Multi-agent systems is about how modelling of artificial agents, agents capable of perceiving input from its environment, shape and follow its goals and interact with its environment which can consist of other agents. It is about modelling and simulation of interaction between agents.
Search and planning algorithms is about intelligent problem-solving, and how one can create goals and develop algorithms that creates a plan to reach a goal based on the agents skill, environment and the resources available for the agent.
Natural language processing is about machine-understanding and manipulation of natural language.
Perception is about developing skills which a digital agent must observe its environment. One of the many challenges is how a digital agent can identify objects in the real world (for example via video, sound, or a picture) and the relation between these objects.
Robotics is about building intelligent physical agents and improve the possibilities to the existing machines. These include industrial robots, everyday-robots, automatic vehicles, and autonomous systems in general.
Candidates after finishing should have the following learning outcomes:
Knowledge:
Skills:
General competence:
General study competence and MATRS (R1 or S1+S2) (Norway)
Higher Education Entrance Qualification (With some math) (Other)
The bachelor degree in artificial intelligence is a specially arranged study-program with an estimated time frame of three years, equivalent of 180 credits. All subjects in the program is mandatory, and the student should take them in the order which is decided by the board for the bachelor.
The degree consists of the following subjects which are all mandatory (the credit number in parentheses):
2. Semester, spring:
3. Semester, autumn:
4. Semester, spring
5. Semester, autumn:
One of the following subjects (10 credits):
Information science:
Informatics:
6. Semester, spring:
Two of the following subjects ( 20 credits):
Information science:
Informatics:
Through the degree in Artificial Intelligence, you gain both work related IT-competence and an academically skill to critically analyse and think. It will give you a double competence which is highly sought after on the job market. The degree qualifies for teaching and work in different subjects¿ dependent on the specialization you choose as part of the third year of the degree.
The degree can also be extended into a master¿s degree in multiple directions which qualifies for research and teaching within the university and higher education sector.
In the final part of the degree, you can specialize according to your interests. You can choose to learn more about machine learning and programming, which is sought after in many positions in the industry and in public sector. You can also orient yourself more towards research within the field of Artificial Intelligence, which will give you skills which is sought after in companies which invest on new technology in artificial intelligence or automatic systems.