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Towards data mining

Individual course

Max amount of FITech students: 30

Amount and quality of data plays a major role in modern machine learning applications. In this course the students are familiarised with different concepts concerning data such as: data gathering, data preprocessing and normalisation, combining data from multiple sources, missing data and outliers.

After this course the student has good capabilities to identify use cases for data that has been gathered in industrial environment or organise high-quality data gathering for new applications.

Teaching methods

There is no weekly schedule, students can study at their own pace. The course needs to be completed by 11.6.2022 (exam and exercises which need to be submitted before taking the exam).

The course has an electronic EXAM that can be completed at selected university campuses all around Finland. Read more about EXAM here.

More information in the University of Oulu study guide.

You can get a digital badge after completing this course.

datanlouhinta datan kokoaminen poikkeavat arvot esikäsittely koneoppiminen tekoäly machine learning artificial intelligence R-kieli R language

Responsible teacher

University of Oulu
Satu Tamminen
satu.tamminen(at)oulu.fi

Contact person for applications

FITech Network University
Monica Sandberg , Student services specialist
monica.sandberg(at)fitech.io
Start here
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Category:
ICT Studies
Topics:
AI and machine learning,
Data analytics
Course code:
521156S
Credits:
5 ECTS
Price:
0 €
Level:
Teaching period:
14.3.–10.6.2022
Application deadline:
6.3.2022
Host university:
University of Oulu
Study is open for:
Adult learner,
Degree student
Teaching methods:
Blended
Language:
English
General prerequisites:
Basics of statistical mathematics. Basics of artificial intelligence and machine learning are beneficial.
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This course is included in the following themes