Nice and simple to follow introductory course on the topic. My only critic would be relying exclusively on R: some python code (both "by hand" and through some packages) would have been great.

Very easy to follow examples and great coverage for such an important topic! The delivery sometimes get repetitive and I wish we talked more about how the uncertainties are derived.

A high quality course that delivers what it says in the title. Well-paced introduction to the potential outcomes framework, with a nice balance of theoretical and practical aspects.

It will be better to give reviews of related applications in specific AI areas (e.g, computer vision, NLP, etc.) at the end of each of the sections of the lesson.

very good content. Story line is highly concise. However, Lecturer could be more stream-lined the the way of explaining. He sure is a skilled guy, however.

Excellent course. Could use a small restructuring, as I had to go through the material more than once, but otherwise, very good material and presentation.

A consise course on causality; watched on 2x speed because the instructor speaks rather slowly; really bad formatting of quiz questions.

I thought this was a good overview and I'm glad I took the course, but I would have preferred more hands on programming assignments.

Some of the materials are bit academical and away from industry, however, I found most of the materials relevant and practical.

All good and very well explained. Would have liked a mention of how to use the methods in Python or other languages than R

Great course, the title is exactly what you will get: the basics on inferring causal effects from observational data

Great course. I have learned a lot. I just wish to have more programming exercises to cement our knowledge.

The course is very helpful for beginners to understand. Also, to be able to practice through R is helpful.

Could use a bit more guidance on the projects, but overall a helpful course. Gets straight to the point.

Okay, strong focus on methods to calculate causal effect, but not so on model understanding

Interesting introductory course about causality. Good "compilation" in just 5 weeks.

Thanks!

The course is very useful for beginners. The materials are clear and easy to understand.

I really enjoyed this course and I appreciated the practice exercise in R.

They could offer more applied exercises in R. But, it was also great.

The lectures are good, and they might consider covering more topics.

It was well laid out, and overall helpful.

A good course. Bit difficult for novices.

Great

Clear deliver of engaging content. Very disappointed the course lacked an IV program or some capstone to evaluate learning. Why would you complete the course with a quiz compared to a practical assignment. I also do not understand why the slides are not available.

I think it would be nice to have a bit of an overview how the methods compare to others in the field of causal inference. Also the slides could contain more illustrations. However, I liked the selection of the material.