Dec 28, 2017
I really enjoyed this course, the pace could be more even in parts. Sometimes the pace could be more even and some more books/reference material for further study would be nice.
Nov 30, 2017
The material is great. Just wished the professor was more active in the discussion forum. Have not showed up in the forum for weeks. At least there should be a TA or something.
von Leihua Ye•
May 12, 2019
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.
von Xisco Bernal•
May 05, 2019
Very interesting studies.
von Cameron Fincher•
Apr 05, 2019
Good course on the over view of Causality. Not too technical, but not too light and fluffy.
von Wayne Lee•
Mar 17, 2019
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.
von Naiqiao Hou•
Feb 27, 2019
The course is very useful for beginners. The materials are clear and easy to understand.
Feb 19, 2019
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.
von Christopher Rinaldi•
Feb 11, 2019
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.
von Alejandro Alvarez Pérez•
Dec 15, 2018
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.
von Michael Noetel•
Dec 09, 2018
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).
von Mateusz Kobos•
Dec 07, 2018
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.