Introduction to Visual Data Analytics, 7,5 credits
Start of studies
Spring semester 2026
Form of education
Campus, Day-time, Half-time
Language
English
Period
2026 week 14 until 2026 week 23
Admission to the course requires completed courses of an amount of 60 credits of which 30 credits must be in Computer Science and 6 credits in Programming, as well as an attended course in Mathematical Statistics.
Want to make sense of complex data? Dive into Visualization! Visualization is not just about creating eye-catching visuals; it is a powerful tool for get insights, detecting trends, and making data-driven decisions. In this basic level course, you will learn essential concepts in visualization theory and effective visualization techniques to show and analyze data. You will also be practicing programming with relevant visualization libraries in Python and learn how to best visualize data depending on your goal. Visualizing data is a helpful skill to master, and it can be applied in many different areas, for example business analytics, gaming, computer science, environmental science, and e-health. This course will refine your analytical thinking and open new horizons in your career or studies in data analysis.
Admission to the course requires completed courses of an amount of 60 credits of which 30 credits must be in Computer Science and 6 credits in Programming, as well as an attended course in Mathematical Statistics.
Study subject
Computer Science
Level
G1F
Registration code
D5995
Course code
DV1699
