Data visualization
Dates & timetable:
Application for this face-to-face micro-credential is open from April 20 to May 6
| Date | Time |
| 22-26/06/2026 | Detailed timetables will be passed to the accepted students a few weeks before the classes start. All the classes will take place within the dates indicated, no overlaps guaranteed. |
Description:
Master the art of Data Visualization in this practical micro-credential designed for todayโs data-driven world. Discover how people see and understand visual information, and learn how design choices influence the way data is interpreted. Transform raw data into clear, effective visuals that support analysis and communication.
Through real-world examples, explore how to present patterns, trends, and unusual values in data. Strengthen your critical thinking and communication skills, and gain the confidence to present data clearly, responsibly, and with impact.
Learning Outcomes:
- Analyse data visualizations in order to identify patterns, limitations, perceptual issues, and potential sources of misinterpretation.
- Evaluate and design data visualizations that communicate analytical results accurately, clearly, and responsibly for a defined audience.
Sustainable development goals:
- SDG4. Quality education
- SDG9. Industry, innovation and infrastructure
- SDG10. Reduced inequalities
- SDG16. Peace, justice and strong institutions
Sector:
Smart
Thematic area:
Digital humanities
HASHTAGS/KEY WORDS:
#datanalysis #innovations #technologies #statistics
Volume (ECTS):
1
Language:
English
Hard skills:
Designing and selecting appropriate data visualizations based on data type, analytical goals, and perceptual principles Analyzing and interpreting visual representations of data, including distributions, outliers, correlations, and regressions
Soft skills:
Designing and selecting appropriate data visualizations based on data type, analytical goals, and perceptual principles Clear and responsible communication of complex information to diverse audiences
Study format:
Face-to-face, La Rochelle Universitรฉ, 22-26/06/2026
Study methods:
Lectures Guided analysis In-class demonstrations and collective critique sessions Individual reading of reference materials, practice on several visualization tools Live demonstrations of visualization creation and improvement Practical sessions focused on distributions, outliers, correlation, and regression Peer discussion and feedback
Hours
Synchronous contact hours: 10
Asynchronous hours & self directed learning: 15
Entry requirements:
Bachelor student in one of the 9 partner universities of EU-CONEXUS, providing a proof of English proficiency of at least B2 level (certificate or online test).
Assessment:
- Written analytical assignment
- Continuous assessment through in-class visualization critique excercises
- Practical project combining visualization design and justification
- Written presentation of design choices
HOST UNIVERSITY:
La Rochelle Universitรฉ, France
Stage of accreditation:
Institutional accreditation
