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Data Visualization for and with AI

Micro-credential

September 2025 – December 2025

Data visualization is used to communicate statistics and information in a visual manner. This is used frequently in research & engineering, in evidence-based methods (decision and policymaking) and in multiple stages of the development and deployment of data- and AI-driven systems.

This course is situated uniquely at the intersection of data visualization & AI systems. In this course you will learn about the different aspects of data visualization, current best practices, and gain experience in hands-on use of (programming) tools to create data visualizations and dashboards.

Specific attention will be paid to the use of data visualization in development and deployment of AI systems. This includes techniques for interactive exploration of data and improvement of the quality of data and machine learning models. We review methods such as dimensionality reduction, outlier detection, bias/fairness assessment, and XAI methods. Notably, we also survey the converse: (Gen)AI methods to automate the data visualization process itself.



This course is targeted at professionals that are involved in the broad sense in development processes of systems for decision-support or automation that include AI components, and who wish to advance their skills to develop, evaluate, and deploy high-quality data visualizations and dashboards.

Most participants will have a background in engineering or computer science, but the course is open to people with a different background who have experience with the following:

  • Have basic programming skills in Python
  • Have knowledge of and the ability to apply basic machine learning algorithms
The language of instruction is English, which requires a sufficient command of the English language.


Micro-credentials are small courses of academic level that focus on specific competencies. They often consist of one or several subjects which are also taught in an university bachelor's or master's degree.

If you pass the micro-credential, you will receive a certificate as proof that you have completed the acquired competencies. So you also acquire real official credits who are recognized in your further career, also internationally. They can also lead to exemptions for other courses, also at other institutions and organizations. You will receive a certificate of the micro-credential + credit certificate when you pass the corresponding exam (3 ECTS points).

Examination method

  • oral assessment, with written preparation during which the internet and course material is available.
  • Continuous evaluation: graded assignments (small projects) in small groups, graded written reports.
  • The final score is the average score for the two parts (50% oral assessment and 50% assignments).


Lecturer

Prof. Jefrey Lijffijt, Department of Electronics and Information Systems, Ghent University



Contents

  • Why data visualization: in general & use cases
  • Theory and principles of data visualization
  • Theory of perception and design mantras
  • Visualization of various data types: time series, maps, and graphs
  • Dashboards, interactive graphs, and tools to develop web apps
  • Visualisation to explore data and AI models, including data quality and bias/fairness
  • AI to automate data visualization
  • Evaluation of (interactive) visualisation
The course consists of lectures and a few assignments in small groups. These assignments consist of the implementation of (interactive) graphs and dashboards using techniques presented in the lectures, and writing a brief written report with critical reflection. Each assignment is introduced in a tutorial seminar, where the necessary tools are introduced. The assignments partially build on each other. Both the implementation and reflection reports are graded and students will receive feedback on them.

Final competences

  • Be able to explain what data visualization is and motivate its use
  • Have knowledge of human perception in the context of data visualization
  • Have knowledge of and be able to apply the theory of data visualization and design principles
  • Appropriately apply existing (semi-automatic) tools for make graphs for different data types and structured data: time series, maps, graphs
  • Be able to design and implement interactive graphs and dashboards (as a web app)
  • Be familiar with the application of visualization in data exploration and the development of AI models, including exploration and improvement of data quality and bias/fairness
  • Critically reflect on (interactive) data visualizations and dashboards and have knowledge on how to evaluate these

Practical info


Fee

341,90 euro

Course material is at the learning platform Ufora.

Click here for more information about the billing process and the payment request.

SME portfolio

Ghent University accepts payments via the SME portfolio (www.kmo-portfolio.be; use authorization code DV.O103193).

Opleidingsverlof (VOV)

This training is recognized in the context of VOV. For each credit point you are entitled to 4 hours of VOV.

This course (3 ECTS points) covers in total 12 hours of VOV (participation at the assigments and the exam is mandatory).

The registration certificate for VOV can be found at your personal page in OASIS (student administration platform).



Enrol here (from August): studiekiezer.ugent.be/2025/micro-credential-data-visualization-for-and-with-ai-en

A manual for Oasis can be found here.



  • Classes start on September 22, 2025 and always take place on Mondays from 10 am till 1 pm in building 126 (IGent), Technologiepark Zwijnaarde (note: paid parking in the street!). The last session will be given on December 8, 2025. Deadlines for the final exercises will be in the week of December 15 and the oral exam takes place in January on dates to be determined.
  • Participants take the classes together with students of the Master of Science in Bioinformatics, Master of Science in Industrial Engineering and Operations Research and Master of Science in Computer Science Engineering.
  • The training is supported by the Ufora learning platform, which contains, among other things, the course material.
  • A personal laptop is required.
  • Exam: oral exam (50%) + assignment (50%)

Organisation

Universiteit Gent
UGent Academie voor Ingenieurs
Secretariaat
 Els Van Lierde
Technologiepark 60
9052 Zwijnaarde
Tel.: +32 9 264 55 82
ugain@UGent.be