* Students understand the philosophy, ethics, and socio-economics of digital technologies, Students understand and learn social/ethical dilemmas, research integrity and legal boundaries in data use,
* Students gain an overall awareness of responsibility in data sciences, learn to implement responsible data analytics projects.
* Students critically assess academic papers/projects through ethical research conduct and investigate research misconduct on data.
* Students have a comprehensive understanding of research integrity, academic ethics and data security.
* Students understand and evaluate the societal implications of changes induced by new technologies, identification of biases and moral issues in the data, or in the algorithms, e.g., in machine learning.
* Students design a data analytics project from scratch and implement it through the perspective of responsible data use, writing policy reports (on security, integrity etc).
* Students work within agile teams that communicate effectively and achieve deliverables fast and efficiently.

This course addresses one of the most important contemporary issues - responsible data use. The concept of responsible data is based on understanding the individual and societal collective duty to prioritise and respond to the ethical, legal and social challenges coming from the use of data. The key elements of the responsible data use - data privacy, data protection and data ethics - are discussed in details. Moreover, the main feature of the course is to bring all these three elements together and to discuss them in context of contemporary legal and technological environment as well as future development. This course will be offered jointly by IDS and DAD.

Formative assessment: Games, group discussions, and feedback during the course on the final project.
Summative assessment: Assignments and final exam
Instructional approach: Tutorials, instructional games, lectures