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.

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.

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

Course was dry, and not very engaging. I did not get much out of it, and it seems like most people only spend a couple of hours taking this course. The labs were more interesting, I had more fun looking at the code that was not explained or part of the course, than learning the actual course material.

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

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.

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.

It just totally rebuilds my mind in thinking about how I should approach solving problems. I feel that I'm learning strong framework for an evidence-based logical approach. Just like a consultant.

This course is not as engaging or organized as well as the first two courses in the Data Science Certificate. I found it to be unnecessarily complicated and confusing due to jumping around a bit in terms of steps in the process.

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 case study given was very confusing. Even, the tutor did not do a great job explaining and facilitating the case study. I only understand it better through the cooking metaphor. They should have choose a better and simpler case study.

This is a proper course which will make you to understand each and every stage of Data science methodology. Lectures are well enough to make you think as a data scientist. Thank you fr this course :)

Except for the lab parts, it is a very poor course which covered a very important topic that should build the initial stone in working as data scientist but the instructors ruined my experience. They were monotonous, did not to explain in simpler ways. they explained from they high end expert and the slides were poor and not interactive and verry boring and it was extremely difficult to keep focus with them.

terrible course

I actually enjoyed this class... I didnt expect to based on the reviews going in, but it was interesting and I did learn a lot. That being said however, the material was a little dry and the case study was a little more complicated than it should be for someone taking an intro class to data science methodology. They may be perfect for someone in the industry, but I spent a lot of time on google looking up what the case study was talking about - I learned a lot more in the labs with food and ingredients and recipes

Fine for an introductory course

More or less a complete waste of time. Some of the Jupyter notebooks were interesting, but not enough to make this anything other than a way to stretch out your enrollment period in the course...

Very informative step-by-step guide of how to create a data science project. Course presents concepts in an engaging way and the quizzes and assignments helped in understanding the overall material.

This is my favourite in the series, the 10 questions to be answered were mind opening. The repetition after every video makes easier for important points to stick to the brain. Very good indeed...

This was a critical course for me. Understanding the data scientists workflow which includes customer\client interaction has help me in understanding how to proceed in future endeavors.

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

excellent training with hands-on exercises

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