Pretty good course, but could have been a little more challenging. I'm glad I learned the process, but I'm ready for some more hands-on work. This was getting close- I think the final projects, especially for week 3, were good practice to apply what I learned.

Appreciate the content so far. This can be though made more in-depth when it comes to hands on. Including graded level hands on practice can enhance the learning experience the students get from this course.

Thanks for enabling us with all through the course.

I understand that this video want to give a full image of Data Science. But its case study including too much low-frequency vocabulary / terminology, which is an obstacle to beginner. And some reading material 's exercise is not very necessary...

I found this course to be a little bit too vague and theoretical, and hence, difficult to understand sometimes. I personally prefer to study and work with hands-on and applied aspects of Data Science instead of theory and vague definitions.

The Videos provided a good overview of the process. But felt like they were extremely short for the concept they were covering. I would have liked them to be a bit longer and illustrated like the ones from the What is Data Science? course.

There's a lot of reading. If there's more hand-on training, that would be great, The tools provided to do exercise sometimes didn't work. I have to loaded several times to complete my work. That delayed my time to complete the course,

I had a few issues with the IBM cloud that could not be addressed quickly. As a result I completed the course without being able to do the all the assignments, so I missed out and did not get all the value I should have from this course.

Videos are somewhat confusing. They are not target to the current topic but also states about other topics as well in the same video, which makes it difficult to understand and easy to loose track of what is being taught in the video.

Presents you a good overview according the main topics of data science methodology. The case study is a good example to illustrate to content. But with respect to my experience the labs are very limited concerning the learning effect.

The narrator was quite fast and I could not engage with the video lectures so well on this course. Consider review the Hospital case study too, which is quite complex when trying to understand the new concepts on the methodology.

The course is a bit confusing for a beginner, the concepts should be clearly explained, the prediction model and the descriptive model should be taken in different videos.The learner should understand the difference clearly.

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.