Data Analysis and Data Mining
Course code
MLM6310.DT
old course code
Course title in Estonian
Andmeanalüüs ja andmekaeve
Course title in English
Data Analysis and Data Mining
ECTS credits
6.0
Assessment form
assessment
lecturer of 2025/2026 Autumn semester
Not opened for teaching. Click the study programme link below to see the nominal division schedule.
lecturer of 2025/2026 Spring semester
Not opened for teaching. Click the study programme link below to see the nominal division schedule.
Course aims
Develop knowledge and skills necessary for conducting Statistical Data Analysis using the R programming language. To learn how to collect and clean data; make
exploratory techniques for summarizing data; to make prediction functions; to cover the basics of machine learning; to learn how to use R for effective data analysis.
exploratory techniques for summarizing data; to make prediction functions; to cover the basics of machine learning; to learn how to use R for effective data analysis.
Brief description of the course
Drawing conclusions about populations, statistical significance tests. Parametric and nonparametric tests, Regression analysis, ANOVA and ANCOVA models.
The course covers the basics needed for collecting and cleaning data, the essential exploratory techniques for summarizing data, the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, and error rates. The course covers program R possibilities for processing data and data analysis. We will cover the plotting systems in R as well as
some of the basic principles of constructing data graphics.
The course covers the basics needed for collecting and cleaning data, the essential exploratory techniques for summarizing data, the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, and error rates. The course covers program R possibilities for processing data and data analysis. We will cover the plotting systems in R as well as
some of the basic principles of constructing data graphics.
Learning outcomes in the course
Upon completing the course the student:
- defines the main concepts of data analysis and data mining;
- describes the main methods covered in the course and solves standard exercises;
- applies the R package to solve typical data analysis problems.
- defines the main concepts of data analysis and data mining;
- describes the main methods covered in the course and solves standard exercises;
- applies the R package to solve typical data analysis problems.
Teacher
Maria Zeltser
Prerequisite course 1
Study programmes containing that course