Introduction to Artificial Intelligence

Undergraduate course

Course description

Objectives and Content

The goal of AIKI100 is to provide a broad introduction to artificial intelligence (AI) as a discipline and to offer a pathway towards further courses and potential specializations. The course introduces the interdisciplinary breadth of the discipline, the historical development and use of ideas within AI research, the relationship between artificial intelligence and society, and the ethical implications of this relationship. The course will also provide an introduction to the most significant results and challenges in the subdisciplines of AI, including knowledge representation and reasoning, multi-agent systems, natural language understanding, machine learning, planning, and search.

Learning Outcomes

After competing the course, the student will have the following learning outcomes defined in terms of knowledge, skills, and general competence.

Knowledge

The student

  • can describe artificial intelligence as a scientific discipline in a historical and societal context.
  • can summarize the most important challenges and results in different subdisciplines of artificial intelligence
  • understands how artificial intelligence is supported by mathematics, information science, computer science, and automation.

Skills

The student

  • can connect different tasks that usually require human intelligence to relevant methods within artificial intelligence.
  • can critically discuss the possibilities and limitations within the field of artificial intelligence in the context of technology and society.
  • can identify their own interests within artificial intelligence and choose a direction for further AI studies.

ECTS Credits

10 ECTS

Level of Study

Bachelor level.

Semester of Instruction

Autumn
Required Previous Knowledge
None
Recommended Previous Knowledge
Mathematical training is an advantage.
Credit Reduction due to Course Overlap
Access to the Course
The course is open to students with admission to study at the UiB.
Teaching and learning methods
Lectures, seminars and group exercises (normally 2 hours each for 11-14 weeks). Students are expected to organize their own working groups.
Compulsory Assignments and Attendance

Mandatory submissions of seminar assignments. They must be submitted during the teaching semester, and 80% of them should be approved.

Choose one between the following.

  • Mandatory participation: attendance at lab and seminar groups (at least 75%)
  • Self-study: complete the mandatory seminar assignments independently within the set deadlines
Forms of Assessment

The assessment consists of a 4-hour written exam.

The exam will be given in the language of instruction in the course.

The answers to the exam must be submitted in the same language as the exam.

Grading Scale
The grading system has a descending scale from A to E for passing and F for failing.
Assessment Semester

Assessment in teaching semester.

A retake exam is arranged for students with valid absence according to UiBs study regulations ยง 5-5. If there is a retake exam for students valid absence, students with the following results/absences can register for the exam:

  • interruption during the exam
  • fail/failed

Students can register themselves in Studentweb after January 15th.

Reading List
The reading list will be ready before the 1st of July for the autumn semester and before the 1st of December for the spring semester.
Course Evaluation
All courses are evaluated according to UiB's system for quality assurance of education.
Examination Support Material
Dictionary preapproved by the Faculty.
Course Coordinator
The Department of Information Science and Media Studies at the Faculty of Social Sciences has the administrative responsibility for the course