Data Analytics and Privacy

Week 1 - Introduction • Chapter 1 from ‘Data Science and Analytics with Python’ by J. Rogel-Salazar • Lecture - 01/11/21 - Fundamentals of Data Analytics/ Science Week 2 - Evolution of privacy & data protection: the interplay of society, technology, and law • Chapter 1, paragraph 1.1 and 1.2 of the FRA Handbook on European Data Protection Law • Lecture - 08/11/21 Week 3 - GDPR : basic portions and fundamental principles 11 • Page 115-159 of the FRA Handbook on Eur...

In this file, I have summarized all the exam-related material. This includes a summary per week of the lecture material along with a summary of the literature and a summery per week of each tutorial. To top that off, in week 6, I have added the tutorial assignment with all the answers (this is highly important for the exam). And in week 7, I have added the mock exam questions with all the right answers. Good luck with the exam ;)

Transparency is a fundamental principle of the GDPR. What does this mean? Can transparency enhancing tools enable transparency?

Detailed notes about the GDPR. Explanation of fundamental principles and rules for processing data. What is the GDPR for? What are the specific sections of the GDPR? What are the values and rationale of data protection laws?

What is privacy? What is data protection? Are they the same thing? What are the legal sources of privacy rights and data protection? What is the difference between the private and public sphere? Who should afford privacy rights and when? Detailed discussion on the issues surrounding privacy and data protection, plus case recommendations.

Detailed notes on privacy by design strategies and implementation. What is privacy? How can security measures be used to achieve privacy? What are rights to privacy? How is privacy ensured in big data?

Introduction to data analytics and science. How do we analyse data? What are data science projects? What is big data? What are the problems of big data?