FYS-2021 Machine Learning - 10 ECTS
Knowledge - The student is able to:
- Describe fundamental concepts behind machine learning in modern society.
- Describe a number of machine learning application areas in society.
- Discuss and select appropriate data sources applicable to a given machine learning approach.
- Discuss and select appropriate approaches, such as unsupervised versus supervised, when it comes to the choice of machine learning algorithm to use.
Skills - The student is able to:
- explain the application domains of machine learning methodology and machine learning algorithms for data analysis in society and research.
- analyse data for knowledge extraction and inference by applying various machine learning methods and algorithms.
General expertise - The student is able to:
- understand the role of machine learning in modern society in the context of data analysis
- implement and apply fundamental machine learning methods and algorithms for analysis of data in e.g. Matlab or Python
There are no academic prerequisites to add this module in your Learning Agreement.
Do you have questions about this module? Please check the following website to contact the course coordinator for exchange students at the faculty: https://en.uit.no/education/art?p_document_id=510412
|Examination systems:||Date:||Weighting:||Duration:||Grade scale:|
|Off campus exam||4/10||A–E, fail F|
|School exam||6/10||4 Hours||A–E, fail F|
|Coursework requirements – To take an examination, the student must have passed the following coursework requirements:|
|Assignment 1||Approved/ Not approved|
|Assignment 2||Approved/ Not approved|
- About the course
- Campus: Tromsø |
- ECTS: 10
- Course code: FYS-2021
- Responsible unit
- Institutt for fysikk og teknologi
- Tidligere år og semester for dette emnet