Syllabus

Module 1 

• Types of data, data formats, and data collection methods - Universidad Complutense de Madrid 
• Computational thinking: algorithms and programming in Python - Università di Bologna 
• Basic statistical properties of data sets, data quality - Uniwersytet Jagielloński w Krakowie 
• Data cleaning, transformation and linkage - Universidad Complutense de Madrid, Uniwersytet Jagielloński w Krakowie 
• Data visualisation and interpretation - Universidad Complutense de Madrid 

Module 2 

• Using simple analytics tools and building narratives - Università di Bologna 
• Providing information to support decision-making - University of Edinburgh 
• Economic and societal value of data and analytics - KU Leuven 
• Ethical and legal aspects, social impact awareness - Universidad Complutense de Madrid, KU Leuven 

For Module 1 and Module 2 online tutoring will be available. This will be provided by the Lead University. 

Module 3 

With this module the participants should reach a basic understanding of what a data science project is. In particular, they should develop the ability to cooperate in groups for the production of simple analyses, and to understand the outcomes of more complicated ones. They should also be able to focus on the path from problems to data analytic solutions and to communicate the results of data analysis. 

The module will be focused on the making of data-driven decisions in healthcare, that is how to use data, analytics and evidence-based insights to improve patient care, optimize operations, and enhance overall healthcare outcomes.