Machine Learning

Studiepoeng, omfang

10 ECTS

Studienivå (studiesyklus)

Bachelor

Undervisningssemester

Spring

Mål og innhald

The course introduces Machine Learning, with a view towards data analysis applications. Topics covered are supervised learning (classification and regression) with deep learning, unsupervised learning including clustering, reinforcement learning, and the practice of machine learning.

Læringsutbyte

A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The candidate

• has theoretical knowledge about the principles of machine learning
• has a basic understanding of the contemporary machine learning algorithms
• has a broad knowledge about the use of machine learning in data analysis, its advantages and limitations

Skills

The candidate

• can analyze and design machine learning solutions for data analysis applications

Krav til forkunnskapar

INFO132 or equivalent. Basic understanding of programming and algorithms.

Studiepoengsreduksjon

INF264 (10 sp)

Krav til studierett

Emnet er ope for studentar med studierett på UiB. Emnet har 200 studieplassar. Studentar som har emnet som obligatorisk i studieplanen vil ha prioritet.

Arbeids- og undervisningsformer

Lectures, seminars and data labs, normally 2 + 2 hours per week for 12-15 weeks.

Obligatorisk undervisningsaktivitet

Participation: compulsory attendance at labs (at least 75%).

Approved compulsory requirements are valid for the two following semesters.

Vurderingsformer

• Group assignment where students demonstrate their ability to analyze and design machine learning solutions (30% of grade)
• 2 hour digital home exam (70% of grade) - multiple choice exam

Hjelpemiddel til eksamen

All written material in paper form is allowed on the exam.

Karakterskala

A-F

Vurderingssemester

Assessment only in teaching semester.

Litteraturliste

The reading list will be ready before 1 June for the autumn semester and 1 Decemeber for the spring semester. 

Emneevaluering

Alle emne blir evaluert i tråd med UiBs kvalitetssystem for utdanning.

Programansvarleg

The Programme Committee is responsible for the content, structure and quality of the study programme and courses.

Administrativt ansvarleg

The Department of Information Science and Media Studies at the Faculty of Social Sciences has the administrative responsibility for the course