Machine Learning

Lågaregradsemne

Studiepoeng
10
Undervisningssemester
Vår
Emnekode
INFO284
Talet på semester
1
Undervisningsspråk
English
Ressursar
Timeplan

Emnebeskrivelse

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

Studiepoeng, omfang

10 ECTS

Studienivå (studiesyklus)

Bachelor

Undervisningssemester

Spring
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 og opptak skjer etter søknad i StudentWeb.

Studentar som har emnet som obligatorisk i studieplanen vil være prioritert.

Søknadsfrist er mandag uke 2.

Du får svar på om du har fått plass på emnet seinast torsdag samme uke som fristen.

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

    • The exam assignment will be given in the language of instruction in the course.
    The exam answer must be submitted in the same language as the exam assignment.

    Karakterskala
    A-F
    Vurderingssemester

    Assessment only in teaching semester.

    Retake exam

    School exam

    A retake exam is arranged for students with valid absence according to § 5-5. If there is a retake exam, this will be available for students with the follow results/absences:

    • Medical certificate/valid absence
    • Interruption during the exam
    • Fail/failed

    If you have the right to take a retake exam and a retake exam is arranged for students with valid absences, you can sign up yourself in Studentweb after January 15/August 1.

    Group assignment

    For the group assignment, Students with valid absence as defined in the UiB regulations § 5-5 can apply for an extended submission deadline to eksamen.infomedia@uib.no. The application must be submitted before the deadline for submission has expired.

    Litteraturliste
    The reading list will be ready before 1 July for the autumn semester and 1 Decemeber for the spring semester. 
    Emneevaluering
    Alle emne blir evaluert i tråd med UiBs kvalitetssystem for utdanning.
    Hjelpemiddel til eksamen
    All written material in paper form is allowed on the exam.
    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

    Emnebeskrivelse

    Kontaktinformasjon

    studieveileder.ifi@uib.no

    Telephone 55 58 90 00

    Institutt for informasjons- og medievitenskap