Laboratory: "data visualization narratives"
A.A. 2025/2026
Learning objectives
The course aims to provide students with a comprehensive understanding of the fundamental principles of data visualization and the crucial role of storytelling in crafting effective data-driven narratives.
Learning objectives are articulated as follows:
- Understand the main principles of data visualisation and the relevance and role of storytelling in creating effective data narratives.
- Develop skills in selecting appropriate visual models for different data types and audiences.
- Familiarise with tools and software used for data visualisation.
- Analyse and critique existing data visualisation narratives to identify trends and best practices.
- Apply knowledge and skills to design a data visualisation project as a team.
Learning objectives are articulated as follows:
- Understand the main principles of data visualisation and the relevance and role of storytelling in creating effective data narratives.
- Develop skills in selecting appropriate visual models for different data types and audiences.
- Familiarise with tools and software used for data visualisation.
- Analyse and critique existing data visualisation narratives to identify trends and best practices.
- Apply knowledge and skills to design a data visualisation project as a team.
Expected learning outcomes
Upon compilation of this module, students will be able to:
- Explain the principles of data visualisation and how it contributes to effective storytelling in data narratives.
- Select appropriate visual models for different types of data and audiences.
- Combine the use of data visualisation tools.
- Analyse and critique existing data visualisation narratives.
- Collaboratively design a data visualisation project on a chosen topic.
- Explain the principles of data visualisation and how it contributes to effective storytelling in data narratives.
- Select appropriate visual models for different types of data and audiences.
- Combine the use of data visualisation tools.
- Analyse and critique existing data visualisation narratives.
- Collaboratively design a data visualisation project on a chosen topic.
Periodo: Secondo quadrimestre
Modalità di valutazione: Giudizio di approvazione
Giudizio di valutazione: superato/non superato
Corso singolo
Questo insegnamento non può essere seguito come corso singolo. Puoi trovare gli insegnamenti disponibili consultando il catalogo corsi singoli.
Course syllabus and organization
Edizione unica
Periodo
Secondo quadrimestre
Programma
Il programma è condiviso con i seguenti insegnamenti:
- [BBL-28](https://www.unimi.it/it/ugov/of/af20260000bbl-28)
- [BBL-28](https://www.unimi.it/it/ugov/of/af20260000bbl-28)
SECS-S/01 - STATISTICA - CFU: 3
Attivita' di laboratorio: 20 ore