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.

Good content. But irregular assignments, most with no feedback. Moreover some exercises could have errors, or at least ambiguous enunciates.

I think there are parts in the course where further discussion is needed.

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