It would nice if case study and lab example would be same to follow more deeper understanding between video class and example .The web scraping example is nice and should be in presentation for understanding purpose.

Difficult being able to apply the final test to the complete module objectives. Though it was good foundation, felt it should be split into several workable modules/stages instead of all 10 methodology steps at once.

All example and cases are related to hospital. Every single subject with different case would be highly appreciated and helpful to others. Hospital case were kind of confusing as i am NEW BEE for data science.

Methodology course should be done at the end of the whole certificate course or at least when the student has a better understanding of all the statistical methods available (regression, machine learning..)

This could be little bit more in detail. The content and the methodology was introduced but could be more in detail about all the analytical approaches available and why we chose decision trees for the CHF.

Good intro, but I felt the introduction to python might have been better before this subject. Could have spent more time on the Labs, seemed more complicated if you didn't have any background in coding.

The course has very little material, it feels like it could be a chapter in a course. I learned a valuable and good methodology though. So the content is good, it just feels like very little contents.

Rather open ended. The main points should be crisper. For example, why is feedback not part of the final assessment , where the keywords repeated in the training and in the final assessment?

The last course jumped to python notebooks which has a lot of coding,while Python language is yet to be covered,I feel the notebook assignment should have followed after the Python module.

This course provides a clear approach to data science methodology. The lab exercises are difficult to open and use, but the case study presented in the instructional videos is informative.

very theoretical topic and hard to follow with case study give, The final assignment is also very unclear on what to expect. This course content needs to be redone by the instructors.

this course is helpful and the video aspect is fine.

how can we have access to the videos covered in each course? i need them for my personal revision. is very important to me please.

As I'm not familiar with US healthcare system, the case study given in this course is very confusing to me as there are many unfamiliar words and terms being thrown here and there.

The final assignment is not very specific. Its's largely open ended and left up to individual discretion. Please make it quiz based or project based, where results are definitive.

The core part of the methodology is not properly covered, it would have been better if the technical information such as tools and the modeling strategies are discussed in depth.

The course was OK but not up-to the Mark,the case study was quite tough to understand,the case study could have been something simpler so that the beginners can understand well.

Using a case study to illustrate the ideas is great. But it will be better if a less complicated example can be used to help following the concepts easier and better understood.

An easier and more relatable case study would exponentially increase understanding. The present one had complex medical terms and added a layer of complexity to the course.

It was very theoretical and, at times, a little boring as well. I was hoping for more of a hands on experience. But it was definitely very instructive and educational.

Since we are following a track, the previous two courses were basic and in this course we came across to lot of data science terminology without proper introduction.

The example provided was not good at all to follow on the concepts. i had a hard time following up with the video since very little time was spent on each concept.

The discussions were too introductory. This would be acceptable had there been links to resources which provided more detailed information on this important topic.

The final assignment is not clear

Data preparation and modeling quite confusing for someone with no prior knowledge in data manipulation and statistical background

COurse provides some initial theoretical information but the practical exercises are ofno use. Proper schedule of practical be followed and the instructions for

Its an important topic for data scientists, but wish it was taught in a more interesting way with multiple examples of different types instead of one case study.