Content, progress and pedagogy of the module

The course provides an understanding of different analytical strategies and their implications for data modelling, including descriptive and predictive approaches. It also provides hands-on experience with different data visualization techniques and their analytical contributions.

Learning objectives

Knowledge

In this module students will acquire knowledge of:

• Descriptive analytics, such as social network analysis and dimensionality reduction
• Predictive analytics, such as regression and machine learning
• Techniques for data visualization.

Skills

In this module students will acquire skills in:

• Conducting data-driven analysis
• Conducting participatory data design with users
• Identifying, comparing, and selecting relevant techniques for describing and analyzing data about user behavior, interaction, and/or opinions
• Selecting the optimal data visualization techniques for describing and analyzing digital trace data.

Competences

In this module students will acquire competences in:

• Applying analytical tools to real-world cases
• Taking an analytical, reflective and critical approach to the analysis, visualization, and interpretation of collected research data.

Exam

Exams