I would prefer that the examples be expressed with statistical and mathematical calculations

Não gostei muito da didatica do instrutor e os slides não ajudam no entendimento

Explanations in videos qere not very clear nor very well connecetd with the Quiz

Would have liked a bit more examples and math in some cases. Others were fine.

A bit less engaging than the other parts of the Executive Data Science course.

good content but could be simplified and presented in a more focused man

Would like to have simpler examples to understand some of the concepts.

It was quite hard with all the statistical jargon. Too much theory.

This class has more useful materials than previous ones.

Relevant materials, but lecture delivery is rather dry,

Sometimes it was hard to understand what's going on.

The material is too long and boring.

Too short, too expensive.

Technical vocabulary

Very Good Content

Good

I found this course to be notably worse than all of the others in the series. There is very very little practical content provided within the lectures. Way too many summaries or over-views of what's to come next without really getting into the nuances of what is discussed as a course topic. Way too much repetition of the exact same content, there is even repetition of content in this course that was presented in another one of the courses in the series. Many of the examples are purely meant as a comedic aside rather than actually functioning to discuss the topic with depth. E.g. - talking about statistical modeling and putting up a picture of Ben Stiller from Zoolander - then keeping the picture up there for the entire explanation. There's literally a Nic Cage example provided for the confounding factor lecture only for the instructor to say directly after "This isn't actually the best example" - then proceeds to not explain why it was brought up aside from mentioning there's a spurious correlation. Way too much repetition of similar examples - showing photos of a muscular v. skinny Christian Bale. This pop-culturey reference isn't needed in the first place and doesn't need to be shown in triplicate. I don't mind repetition if there is additional nuance or content provided through them, but that isn't the case in this course. I find there is too much focus on side tangents, where the instructor seems to change thoughts mid-sentence but forgets to come back to the original idea. I think that every single video could be cut down by 25%, purely by being more concise, and should include more nuanced descriptions. I found it particularly odd that instrumental variables were noted as a rather clever technique, yet an explanation was intentionally avoided, however an example was still provided. Bringing up a topic, intentionally refusing to define it, then providing an example directly after just doesn't make sense. I think that more time needs to be spent refining the lectures so that they're designed to teach content. It has the feel of someone who's talking about a field to get people interested in it rather than a practical training course. Many key terms are very poorly defined with examples (on many cases the audience is referred to wikipedia for explanations) in which the basics are repetitively explained while the nuances are glossed over. There seems to be an odd theme where summaries and over-generalizations are far too frequent and yet the key terms and how they relate to examples are an afterthought. I don't think the summaries are necessary given the fact that users can literally re-watch every single video and there isn't enough total content to justify a summary in the first place. Additionally, this course also seems to deviate from the others in that there is an assumption that the student has a heavy amount of programming experience already built in (or that's my assumption since many of the term explanations aren't discussed too heavily). Prior lectures break down the basics more and indicate that potential managers should pursue the data specialization courses.

The lecturer seems afraid of the camera and the feedback on the quizzes should be better. Also, the summary readings should have all the information in the presentations, so you can check up everything more easily in one place.

This course for me was the most difficult to understand. Using as example situations with health area was hard to understand how I can apply in my case. But in general, the other courses were very nice for me.

OK content but delivery could be better. Also poor value for money (you pay 49$ for a course you can finish in a few days) versus other Coursera courses that get you much more bang for your buck.

worst course in executive data science specialization, hard to understand concept. specific examples on health researchs are not common to understand

The content was redundant at times, at other the dots that were trying to be connected were to wide apart on the spectrum

It is good but demands statistics and some knowledge in research area.

Too qualitative, I would had liked some hands-on examples.

Not that engaging content.Too much theoretical approach.