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
Further information about the course and studying
Contact person for applications
Data analytics
Degree student
