Courses
Data science
Course overview
This course introduces fundamental statistical concepts and methods, from descriptive and inferential analysis to time series and data visualisation, with practical applications using Python.
Course content
Topics that are covered in this course:
- Basic concepts of statistics, sampling
- Univariate analysis: measures of centre and dispersion, data visualisation
- Probability theory, the central limit theorem, and statistical tests
- Bivariate Analysis: chi-square test, 2-sample t-test, correlation and regression, data visualisation
- Time series analysis
- Applying Python for data visualisation and analysis
Learning outcomes
After successful completion of the course, participants are able to:
- visualise data using the appropriate plots
- create a simple linear model to show the relationship between two or more variables
- calculate some descriptive measures for data using statistical software
- discuss some common models for predicting time series and/or detecting anomalies.
- indicate the importance of testing the accuracy of a model in a methodologically correct way
- quantify and appropriately test the relationship between two variables
Furthermore, they will know:
- basic rules regarding calculating with probabilities
- the properties of some important probability distributions
- some descriptive measures for data
- different types of plots to represent data visually
Enrollment
The enrollment link will be available at the end of June 2026.
Course information
Category
Transversal skills
Format
Online
Target groups
U!REKA students
Academic year
Starting month
Language
English
Duration
A semester
Contact
Organising institution
HOGENT University of Applied Sciences and Arts
Places reserved for U!REKA participants
Limited
Assessment
Online
Credit/degree/certificate
4 ECTS
Course fee
None
Prerequisites
N/A
Level
Bachelor
