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Towards data mining

Individual course

Max amount of FITech students: 30

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

Course contents

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.

Learning outcomes

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

In Spring period only: There is no weekly schedule, students can study the course at their own pace during the teaching period. All assignments has to be finished before the course ends, including the exam.

In Autumn period: Independent studying with weekly assignments or contact teaching.

Moodle exam possibility for FITech students (please be in touch with the contact person of the course).

Completion methods

Available fully online only for FiTech students.

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

Further information about the course and studying

University of Oulu
FITech contact person Oulu

Contact person for applications

FITech Network University
Fanny Qvickström, Student services specialist
Start here
Start here
ICT studies
AI and machine learning,
Data analytics
Course code:
Study credits:
0 €
Course level:
Teaching period:
Application start date:
Application deadline:
Host university:
University of Oulu
Who can apply:
Adult learner,
Degree student
Teaching method:
Teaching language:
General prerequisites:
Basics of statistical mathematics. Basics of artificial intelligence and machine learning are beneficial.
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