I enjoyed the course and learned basics of causal inference. What I missed was more exercises with R in order to gain more practical understanding of the material. In particular, it would be great to have exercises where you get some dataset and your task is to calculate given causal effect and you need to come up with an approach and to execute it. This would mimic more closely problems that you encounter in practice.

Awesome!!! Looking forward to the next one!!!

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

Good introductory course. I wish there were more quizzes (at least another 2 more), testing our knowledge of various formulae for computing IPTW (inverse probability of treatment weights), ITT (intent to treat) and at least one more lab in R

Hard to understand

Over all, this course is extremely helpful for students who are interested in causal inference of observational data. It provides a rather comprehensive list of methods and techniques that we could use to disentangle causal effects, provided with ample supply of exercises and tests. Highly recommended! Will definitely take other courses on similar topics with the same instructor.

Very interesting studies.

Good course on the over view of Causality. Not too technical, but not too light and fluffy.

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.

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

The content is relaxing and easy to understand, yet extremely useful in real life when you are conducting experiments. The well designed quiz each week only takes a little time, but could help you to diagnose problems and remember the key points. I really love this course.

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.

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.

Content was useful for understanding causal inference in a variety of situations. Presentation was sometimes slow even on double-speed. Lectures were generally structured from abstract to concrete, which was much harder to follow than if it were presented in english first and then made abstract (Mayer, 2009).

This course is quite useful for me to get quick understanding of the causality and causal inference in epidemiologic studies. Thanks to Prof. Roy.

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

Thanks!

Well taught, easy to follow but potentially very important techniques

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

no nonsense, in depth and practical

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.

Amazing Course! Really Helpful. I would love to have a similar full-duration course :D

gives thorough basic intro to causal inference

This course is really fantastic for all levels. Very thorough explanations and helpful illustrations. Many thanks for putting this together!

I have an economics background and during my undergraduate studies I took several statistics and econometric courses. The contents delivered in this course complemented my knowledge very well from another point of view. I would definitely enjoy a more advanced course dealing with other methods. The only aspect I would improve is providing the slides for further study. Other courses in Coursera do this and, honestly, I often consult the slides.

The course is ok, but not having access to the slides is very annoying