Things are too fast in this course and many things remain unexplained which makes it difficult for one to understand properly

Too many errors in the code and explanations. Makes it very difficult to understand which is the right procedure/conclusion.

This course focuses a lot on the theory and explanation. However, there isn't much hands-on practice for the coding itself.

*No response to some questions/comments on the forum

*More details/thorough clarification required for some points covered

There are many errors and this was even the toughest course I have taken yet since many things were not explained clearly

Course is flawless but when i had a technical challenge the Coursera team were clueless on how to fix it.

Otherwise good.

Few of the video requires improvement in terms of its quality. Particularly the lectures corresponding to week 4 and 5

Too complex for easy understand. Should have some documentation explaining the process and comparing the new methods.

It is okay in the sense that you learn something but the questions should be harder and it should go more in depth.

Topics covered are important but videos end abruptly as if narrator was saying something more and video just ended

why is sharing of the notebook worth 3 points? That has absolutely nothing to do with python or data analysis!

Model creation and analysis part are too short, should have more details to understand the concepts better.

This course seems to have an exponential increase in a learning curve. It seemed to be all over the place.

Will be easy if you have prior experience with Python/statistics. I don't and I didn't learn much at all.

More explanations would be great. Its very difficult to understand Data exploration / evaluation sections

Creo que le hace falta unas guías, toda la información se da por videos. Recomendado para principiantes.

As always, the final project always ruins good courses. LAZY design of the projects is unacceptable.

Week 4 is somewhat hard to follow - Here, an overview over the different concepts would really help

I would like to see a final project in this course. It will encourage the learners to do more work.

The week 4 lab had issues with pipelines and did not function well and the final exam locked up.

Needs more information on statistical tests. Specifically, when to use one model over another.

Videos in this section could be little more descriptive. It was not in the pace of a beginner.

It was cool to see the stuff at work but I need more hands on practice to really learn stuff.

This looks good for experienced but not the best of course for beginners/intermediate level.

when it got to model development it got too complicated too fast. The first half was great.