Programplaner og emneplaner - Student
MALK5920 Masteroppgave Emneplan
- Engelsk emnenavn
- Master's Thesis
- Omfang
- 40.0 stp.
- Studieår
- 2025/2026
- Emnehistorikk
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Innledning
Emnebeskrivelsen finnes kun på engelsk. Velg engelsk versjon av nettsiden for å se fullstendig emnebeskrivelse.
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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.
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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.
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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.
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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.
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Vurdering og eksamen
Oral examination, individual.
The exam cannot be appealed.
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Hjelpemidler ved eksamen
None.
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Vurderingsuttrykk
Pass or fail.
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Sensorordning
Two internal examiners. External examiner is used periodically.