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Duration

September 2026 - April 2027

Application deadline

June 1, 2026

Language

English

Price

24.000 kr.

Course provider

Aarhus University

Credit points

15

Learn to make complex data readable and to discover the unexpected in your data set

Visual analytics combines automated analysis techniques with interactive visualizations for an effective understanding, reasoning and decision making based on very large and complex data sets. Following this two-sided approach to data analysis, this course offers a practical introduction to Visual Analytics in three parts – each corresponding to one of the three single subjects, the course consists of:

  • the automated data analytics techniques – especially supervised and unsupervised learning,
  • the interactive visualization techniques – especially for uni-, bi-, and multivariate data.
  • the effective combination of both in a practical visual analytics system as a course project.

Participants develop familiarity with key concepts in data mining, visualization methods, and their mutual integration into visual analytics.

Practical skills include understanding relevant terminology, utilizing state-of-the-art libraries and toolkits, and evaluating visual analytics solutions. The course emphasizes analytical and conceptual proficiency, process knowledge, and effective communication of requirements and results.

NB: This course is taught in English. PhD students will participate in parts of the course. Finally, be aware that the course is still under development. Therefore, we reserve the right to make changes to the description of the course.

Watch the video about Visual Analytics 

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Target group 

This course is relevant for:

Developers of business intelligence (BI) solutions seeking to learn the intricacies of developing a complete BI solution.

Business intelligence architects aiming to acquire a profound understanding of the technologies and thereby design optimal solutions for specific business needs.

Data Scientists or Data analysts, who analyze data on a daily basis, but want to acquire new knowledge about how the underlying technology functions.

Specific admission requirements for Visual Analytics

Participants are expected to have a basic understanding of functions, distance measures, vector and matrix operations, probabilities, descriptive statistics (mean, std. deviation, etc.), and should be familiar with Python and basic web programming.

Based on individual assessment, exemptions from the admission requirements may be granted if it is deemed that you have equivalent educational prerequisites to complete the program. Exemption from the requirement of two years of relevant professional experience after completing the qualifying education is not possible.

If you do not meet the formal admission requirements, please contact Continuing Education for further guidance.

Read more about the general admission to the Master in IT, specialization in Software Construction here.

Single subjects 

The course, Visual Analytics, consists of three single subjects:

  • Data Analytics 
  • Foundations of Visualization
  • Research and Development Project in Visual Analytics 

Vejledning

Questions regarding the curriculum:

Associate Professor Hans-Jörg Schulz
E-mail: hjschulz@cs.au.dk

Questions about admission, enrollment, and billing inquiries: 

Continuing Education, Administration Centre Nat-Tech
E-mail: evu.nat-tech@au.dk

Admission officer, Sabine Louisa Haxen
Phone number: 9352 2803

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