- What are Ethics?
- History, Concept of Informed Consent
- Data Ownership
- Data Validity
- Algorithmic Fairness
- Societal Consequences
- Code of Ethics
Without going into depth on the above I will simply note that the course was almost all lectures with exercises at the end of each module. I found the lectures to be a bit too detailed and cumbersome to follow. So what I did was download the text of each lecture, saved it in a document and read through it.
The material is softer meaning it is not hard core programming or statistics, it is all about the ethical side of data science, manipulating data, ownership of data, privacy and issues relating to these. Personally I would say that although the subject is interesting it is not presented in the best way. Simply talking to an audience is not very captivating with all of the presentation methods available nowadays.
However, the topics are thoroughly covered and the material is straightforward and easy to go over. I would recommend the course to anyone with real interest in the topics but you might want to read through it instead of listening to the lectures as noted.