This one is fairly painful to sit through and needlessly complex. Other sites have explained this much simpler and clearer than here

1) This descriptions in this course are very dull. They need to be supported by better examples which do not include a lot of terminology specific to the topic.

2) The questions in the videos can be better designed to evaluate the students' knowledge about the topic, e.g., letting them apply their knowledge in new examples. Some questions are redundant such as the name of the person who designed the data science methodology or questions specific to the case study and does not necessarily provide insight into general concepts.

3) Simply reading what is in the slides is not a good use of videos and cannot keep the focus of the students for a long time.

4) This course might be located after the Python for Data Science course or even later so that the students could have a more meaningful final assignment, actually applying what they learned on a small data set.

5) Knowing a subject and teaching a subject are two different things. I hope you consult a university professor in the field about how to teach these courses. There is a lot of room for improvement in terms of the pedagogical perspective.

Instead of CHF the case study should be change to something which everyone can understand.

Really difficult content to digest without much written information. This course needs to provide more readings and the videos need to provide more text, as opposed to relying on voice instruction.

This was a good course. It was an overview of the entire data science process, which was helpful for me since I didn't really have a good understanding of what data science meant before this class. Now I have a much better understanding of what people mean when they say data science. Also, this class gives a good orientation for other courses; for example, I would see "data mining" courses on Coursera and not understand how that fit in with data science. Now I do. I would recommend this course for people very new at programming and data science, like me.

The example should change to a easier one. This example is hard to understand.

Quizzes quiz on material not covered in the course or directed to externally. Most of the quizzes are word games and do not apply concepts covered in the material. Everything from how disconnected the quiz questions are compared to available information provided in the course to the peer-graded final assignment show little or now effort was put into composing this course.

Fine for an introductory course

Nothing is discussed in details. For people know nothing about data science, many topics are not explained and they won't understand anything valuable; for people already have a background in data science, the topics are useless and too shallow.

this course should be a little later in the IBM sylalbis

Great description of the Data Science Methodology to apply to have the results needed.

Capstone project is a bit limited on 3 topics to choose from.

Why not more creative or even let the user come up with his own problem !!

Still you do learn a goo methodology to handle a problem with datascience approach

This is course suits anyone who do not have Data Science background, using practical examples & it is easy to understand.

more explanation is needed.....example of hospital is not so easy.

Very boring

The final assignment had me ham strung. You are supposed to do each of the 10 steps at the end, with very little guidance on HOW. The there are specific methods shown but what if they don't fit your final assignment example?

Awesome!

The peer review system is just awful. It takes ages to get graded/be able to grade others and the peers might not demonstrate language level required for grading an essay-type assignment.

This course helped me to get to know data science methodology.

I thought that the material was certainly important, but felt that the quizzes were more memory of the videos rather than an intuitive understanding of the material. Maybe more case studies, or a less complex one might make the material more easily digestible.

This is a great course in which we learn all the steps, one-by-one, to face a problem using data science methodology.

very nice way of explaning the course

Best Course, If you want to learn how the data science applied to the business or general problem

good knowledge gained

too much information on slides. Use more pictures for visualization.