Applied Data Science

Class semester
2nd semester
Class type
Charilaos Akasiadis

Topics per week

1. Scientific method overview

2. Hypotheses and testing

3. Risks in hypothesis testing

4. Scientific error and scientific lies

5. Reviewing scientific work: the peer reviewing process; how to do a good review; how to review one’s own work.

6. Communicating scientific results: clarifying science; risks in publication of results

7. Legal and ethical issues overview: overview of legal and ethical risks

8. Data licensing, sharing, openness: how to share or reuse data; licences and their meaning

9. Emerging data formats and publishing (nano-publications; semantic web)

10. Anonymization and profiling: data aggregation and anonymization; discovering user identity through profiling

11. Privacy and Security concerns: difference between privacy and security; privacy in data publication; sensitive data

12. Ethics considerations in data analysis: the effect and impact of scientific discovery; ethics and data analysis

13. Social understanding of data and ethics