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Machine learning: Basic principles

Individual course

Max amount of FITech students: 40

Persons without a valid study right to a Finnish university have preference to this course.

The course deals with basic principles needed to understand and apply machine learning models and methods. The topics include supervised and unsupervised learning, Bayesian decision theory, parametric methods, tuning model complexity, dimensionality reduction, clustering, nonparametric methods, decision trees, comparing and combining algorithms, as well as a few applications of these methods.

After the course, the student is able to apply the basic machine learning methods to data and to understand new models based on these principles.

More information on Aalto University’s WebOodi page.

You can get a digital badge after completing this course.

Further information about the studies

Aalto University
FITech ICT contact person
fitech-sci(at)aalto.fi

Contact person for applications

FITech
Pilvi Lempiäinen , Service designer
pilvi.lempiainen(at)fitech.io
Start the application process
Start the application process
Category:
ICT Studies
Topic:
AI and machine learning
Course code:
CS-C3210
Credits:
5 ECTS
Level:
Teaching period:
10.9.–24.10.2019
Application deadline:
3.9.2019
Host university:
Aalto University
Study is open for:
Adult learner,
Degree student
Teaching methods:
Blended
Place of contact learning:
Espoo
Language:
English
General prerequisites:
Basic knowledge of data science (e.g. course Data science CS-C3160).
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