De elektronische studiegids voor het academiejaar 2026 - 2027 is onder voorbehoud.





 (9854)

Coordinating lecturer:Prof. dr. Inigo BERMEJO DELGADO 
Member of the teaching team:Prof. dr. Inigo BERMEJO DELGADO 


Credits: 3,0
Study load hours: 81
Period: semester 2 (3sp)

Language of instruction: English
Exam contract: not possible

2nd Chance Exam1: Yes
Final grade2: Numerical
Tolerance3: See included in these programmes

Sequentiality
Mandatory sequentiality bound on the level of programme components
 
 
  Following programme components must have been included in your study programme in a previous education period
    (9847) 3.0 stptn  
 


Content

In data science, even the most powerful insights can fail to make an impact without clear communication. This course explores the art and science of data visualisation, guiding students through the principles of effective visual design to transform complex datasets into clear, compelling stories where intricate ideas become intuitive. 
Content
- Fundamentals of data visualisation
- Overview of data visualisation techniques
- Principles and process of design
- Storytelling with data



Compulsory course material
 

All course material (course notes, handouts, video lectures and exercises) will be available on Blackboard.



Organisational and teaching methods
Organisational methods  
Distance learning  
Project  
Small group session  


Evaluation

Semester 2 (3,00sp)

Evaluation method
Written evaluation during teaching period100 %
Homework
Peer review
Take-home assignment

Second examination period

Evaluation second examination opportunity different from first examination opprt
No


Learning outcomes
  EC = learning outcomes      DC = partial outcomes      BC = evaluation criteria  
Master of Statistics and Data Science
  •  EC 
  • The student can work in a multidisciplinary, intercultural, and international team.

     
  •  DC 
  • The student is able to extract user tasks from domain experts.
  •  EC 
  • The student is able to correctly use the theory, either methodologically or in an application context or both, thus contributing to scientific research within the field of statistical science, data science, or within the field of application.

     
  •  DC 
  • The student is able to correctly use the theory methodologically, thus contributing to scientific research within the field of statistical and data science.

  •  EC 
  • The student is capable of acquiring new knowledge.

  •  EC 
  • The student knows the relevant stakeholders and understands the need for assertive and empathic interaction with them.

     
  •  DC 
  • The student can identify relevant stakeholders and their interests, particularly within the programme specialization.

 

Included in these programmesTolerance3
N
Y



1   Education, Examination and Legal Position Regulations art.12.2, section 2.
2   Education, Examination and Legal Position Regulations art.15.1, section 3.
3   Education, Examination and Legal Position Regulations art.16.9, section 2.