EPN-V2

MALK5920 Masteroppgave Emneplan

Engelsk emnenavn
Master's Thesis
Omfang
40.0 stp.
Studieår
2025/2026
Emnehistorikk
  • Innledning

    Emnebeskrivelsen finnes kun på engelsk. Velg engelsk versjon av nettsiden for å se fullstendig emnebeskrivelse.

  • Forkunnskapskrav

    All courses included in the specialisation must be completed with pass grades and all coursework requirements must be approved before the candidate may submit the master’s thesis.

  • Læringsutbytte

    Students who complete the course are expected to have the following learning outcomes, defined in terms of knowledge, skills and general competence:

    Knowledge

    On successful completion of the course, the student has:

    • an in-depth understanding of machine learning in its main forms: supervised, unsupervised, and reinforcement learning, both theoretical and applied, to solve real- lifeproblems.
    • knowledge and understanding of the main concepts of deep learning.
    • knowledge and understanding of some major concepts in artificial intelligence, including: complex systems (network models, cellular automata, and agent-based models) and evolutionary computing.

    Skills

    On successful completion of the course, the student can:

    • apply techniques from machine learning to real-life problems.
    • analyse data sets with the aid of machine learning algorithms.

    General competence

    On successful completion of the course, the student can:

    • use libraries for programming deep learning algorithms such as TensorFlow.
    • deploy models to relevant real-life problems.
    • solve computational problem using evolutionary computing.
  • Arbeids- og undervisningsformer

    Each module will be taught in a series of lectures. At the end of each module, the students will be assigned a small project to be submitted within a given deadline.

  • Arbeidskrav og obligatoriske aktiviteter

    The following required coursework must be approved before the student can take the exam:

    Compulsory assignments must be approved prior to the exam. The students must submit a small project at the end of each module. All five projects must be approved before examination.

  • Vurdering og eksamen

    Oral examination, individual.

    The exam cannot be appealed.

  • Hjelpemidler ved eksamen

    None.

  • Vurderingsuttrykk

    Pass or fail.

  • Sensorordning

    Two internal examiners. External examiner is used periodically.