學生對 IBM 提供的 Data Science Methodology 的評價和反饋

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

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.

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.

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.

This Course is pretty good and concepts are so nice but the example taken to describe the Data Science Methodology is not so good. Could have been taken a better example with far better presentation skills.

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.

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.

The base concept for every Data Scientist and taught excellent here in Coursera.

The example should be easier than CHF in the videos like the example of cuisines was. The CHF example was good but it was not self explanatory and it might be hard for some people.

this course should be a little later in the IBM sylalbis

Fine for an introductory course

Was a bit hard to understand for a complete beginner without a statistical background. Hospital example was a bit difficult to follow as well.

Too complex of a case study to understand stuff. Also, too boring and theoretical and very less interactive.

excellent training with hands-on exercises

Very well structured course which gives us good insights on data science methodology.

Excellent course and practice. Very complete for those who start in data science.

The Final Assignment was not so easy to understand how to do it.

Excellent description of the processs

Very well explained !!!

The topics covered in this course are really good. Without this course, the training in data science is incomplete

the course should include more hands on tutorial

Case study throughout the course was great idea, i loved it

Wasnt so easy peasy,I appreciated the challenge.