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Data analysis and knowledge discovery
Individual course
Course contents
The course introduces methods and algorithms for extracting information and knowledge from datasets. This includes techniques for visualisation, classification, regression, outlier detection, rule induction, model complexity selection, and model validation.
Learning outcomes
This course enables students to learn when and how to apply state of the art data analysis and knowledge discovery tools for data. Students will learn modern data analysis methods and algorithms to discover patterns and trends in large, complex and high-dimensional data sets, and turn data into information and knowledge.
Teaching
Lectures on campus.
More info on University of Turku’s study guide.
You can get a digital badge after completing this course.
data-analytiikka, visualisointi, luokittelu, regressio, poikkeamat
Responsible teacher
University of Turku
Antti Airola
antti.airola(at)utu.fi
Contact person for applications
FITech Network University
Fanny Qvickström, Student services specialist
info(at)fitech.io
Application period has ended
Category:
ICT studies,
Technical studies
Technical studies
Topics:
Data analytics,
Industrial engineering and management
Industrial engineering and management
Course code:
TKO_3103
Study credits:
5 ECTS
Price:
0 €
Course level:
Teaching period:
23.10.–17.12.2023
Application start date:
21.06.2023
Application deadline:
Application period has ended
Host university:
University of Turku
Who can apply:
Adult learner,
Degree student
Degree student
Teaching method:
Contact
Place of contact learning:
Turku
Teaching language:
English
General prerequisites:
Python programming skills. Basic knowledge of probability, statistics and linear algebra is beneficial.
