Machine Learning
- Studiepoeng10
- UndervisingssemesterVår
- EmnekodeINFO284
- Talet på semester1
- SpråkEnglish
- Ressursar
Hovedinnhold
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
Kontakt
Telephone 55 58 90 00
Eksamensinformasjon
Vurderingsordning: Gruppeoppgave og heimeeksamen
- Trekkfrist
- 19.04.2023
Eksamensdel: Gruppeoppgave
- Innleveringsfrist
- 03.05.2023, 14:00
- Eksamenssystem
- Inspera
- Digital eksamen
Eksamensdel: Flervalgsprøve
- Oppgave utleveres
- 22.05.2023, 09:00
- Innleveringsfrist
- 22.05.2023, 11:00
- Eksamenssystem
- Inspera
- Digital eksamen