Laboratory: "data Visualization Narratives"
A.Y. 2024/2025
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.
Lesson period: First trimester
Assessment methods: Giudizio di approvazione
Assessment result: superato/non superato
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
SECS-S/01 - STATISTICS - University credits: 3
Laboratory activity: 20 hours