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Name of qualification

Bachelor in Artificial Intelligence

ECTS Credits

Estimated time for the degree is three years (180 credits)

Full-time/Part-time

Full-time

Language of Instruction

Norwegian / English

Semester

Autumn

Objectives and content

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:

  • To construct and evaluate hypothesis about how one can create digital agents
  • To design, build and experiment with computer systems that can perform tasks we often think requires intelligence.
  • To utilize the results from the previous mentioned points to improve the functions of existing digital and robotic systems.

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.

Required Learning Outcomes

Candidates after finishing should have the following learning outcomes:

Knowledge:

  • Have a wide theoretical understanding on how Artificial Intelligence-supported systems (AI-systems) work and is constructed.
  • Understand how one can program and experiment with AI-systems with the help of methods from machine learning, symbolic reasoning, and algorithmic-analyses.
  • Understand how technical Artificial Intelligence solutions can have ethical relevance for society and the individual.

Skills:

  • Be able to program new Artificial Intelligent systems and experiment with existing systems.
  • Be able to analyse, describe and solve a problem by utilizing Artificial Intelligence-methods
  • Be able to evaluate a Artificial Intelligent-system with special care to how it can be performed responsible, be transparent and take balanced decisions.
  • Be able to explain Artificial Intelligence-theory to non-professionals.

General competence:

  • Be able to contribute as a ICT-system developer in different types of roles. Ranging from everything from communication with the users to advanced technical development.
  • Be able to cooperate both in group- and project-work.
  • can formulate written reports and documentation and be responsible for oral presentation of own work.

Admission Requirements

General study competence and MATRS (R1 or S1+S2) (Norway)

Higher Education Entrance Qualification (With some math) (Other)

Introductory Courses

AIKI100 is a mandatory introduction-subject in the degree bachelor in artificial intelligence.

Compulsory units

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):

  1. Semester, autumn:
  • AIKI100 introduction to artificial intelligence (10 credits)
  • INFO132 introduction to programming (10 credits)
  • MAT105 Mathematics for Natural Sciences (10 credits)

2. Semester, spring:

  • AIKI110 artificial agents (10 credits)
  • INFO104 Formal methods in information science (10 credits)
  • MAT121 Linear Algebra (10 credits)

3. Semester, autumn:

  • Examen philosphicum (10 credits)
  • INFO180 Methods in Artificial Intelligence (10 credits)
  • INFO282 Knowledge Representation and Reasoning (10 credits)

4. Semester, spring

  • Exchange semester / optional subjects (30 credits)

5. Semester, autumn:

  • AIKI210 Ethics in Artificial Intelligence (10 credits)
  • INF264 Introduction to machine learning (10 credits)

One of the following subjects (10 credits):

Information science:

Informatics:

6. Semester, spring:

  • AIKI200 Bachelor Thesis (10 credits)

Two of the following subjects ( 20 credits):

Information science:

Informatics:

If the students wish not to take one of the two available specializations (information science and informatics), they can apply to choose other subjects in fifth and sixth semester. They apply to their study counselor before the beginning of the fourth semester. The program board will then evaluate your application.

Study period abroad

Today there are many options for you to study abroad. University of Bergen have a lot of cooperation agreements with universities, institutions and organizations in many different countries and regions. It is specifically advised and optimized for this degree to do it in the fourth semester of the degree.

Teaching and learning methods

The teachings will normally consist of lectures, seminars, and computer-lab-seminars.

Assessment methods

The subjects in this degree will mainly follow different combinations of the following exam set ups: Written school exam, oral exam, graded assignments, and folder evaluation.

Employability

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.

Evaluation

All degrees and subjects will be evaluated according to UIB's quality system for education

Administrative responsibility

The faculty of social science with the department of information Science and media studies have the administrative responsibility for this degree.