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-verkostoyliopisto
Fanny Qvickström, Opintoasioiden suunnittelija
info(at)fitech.io

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