It's sometimes difficult to follow professors beacuse they take for granted information about the examples they use that is not evident for the learners. They should take a minute to explain a little bit more what the examples consist of and what are the charts they show. As it happens when Brian Caffo explains the blocking adjustments part.

I found this course used a lot of jargon without explanation. It seems like the instructor understands the content so well that he assumes a level of knowledge from students that do not match the expectations of the rest of the content in this track. At the same time I found the content well presented.

This course is an excellent effort to document the issues faced in real-life data science. However, the flow of the videos seems to be a bit confusing and some of the content is explained in a weird manner.

I missed several concepts to better understand some of the discussions and explanations. It was valid, but I think the statistics background should be better explored.

The course is valuable but highly focussed on scientific applications (inference) and less on business application (i.e. prediction). I hoped for a more even mix.

It was good, but the content is harder to understand in this course.

I would prefer a similar format and emphasis as the other two last courses.

The video quality and content were good. Unfortunately, there were a lot of spelling errors and grammatical mistakes in the written portions.

Very difficult and time consuming course which contains a lot of technical words and jargon. Not recommended for the average beginner.

I would drop some of the cartoons. They are funny but they seem to distract Bryan and overall it's distracting for us students too.

First of all it's too tough to understand but day by day I understood something I got it ..tq.it is very helpful for my studies

There is a lot of technical jargon covered which made the course more challenging than the other courses in the series.

It wasn't as focus on Managing Data Scientists as I was expecting, but rather focus on tips for Data Scientist.

Much theorical with few examples. Could incorporate examples outside the health world as well.

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.