Good overview of a "scientific method" applied to the field. this might be a better choice for the introductory course in the certificate program.

Overall a good beginning course for data science methodology. Some of the steps and processes could have been explained definitions/explanations.

Grading procedure is very weak and course has synchronization of lack of lab and theory. The lab seems very difficult with lots of python coding.

It could be much more interesting if we had the image of someone explaining, if we could see someone, that could show excitement on the subject.

All steps of data science methodology are explained very well. Final assignment could have been more challenging (with some more quiz questions)

This course is really very helpful for upcoming data scientists. i enjoyed a lot this course and i hope this will give me benefit in future.

simple but not easy. But I would like it if they could include a written assignment in between the course too before the final assignment.

In my opinion the first three courses of the IBM Data Science professional certificate can be neatly combined into an Introductory course.

I really appreciate the methodology and how to use it

asort of check list at the end to emphazise the relevant point will be a great plus

Data science methodology is clearly explained with example. Voice in the video is bit, it could be improved. Great course for beginners.

Very good examples to understand each phase of the methodology. Just include example for each type of approach would be five stars rate.

This thing here is VITAL! I would loved this to be bit more hands on. But i guess learned will be applied more closely in next courses.

A very good framework to guide the analysis. I think it's better to put it just after the orientation session while before the tool.

Hi I found this course useful though there can be better example than food and linking of python at lab rite away was more confusing

This could've been condensed down immensely, but I suppose it's something you deal with when sorting through data for data science.

The course was very informative I just wish it went into a little more detail of the statistical tests used in the methodologies.

It's quite clear and interesting course. What lack is a reference to additional reading to give more overview about the subject.

It would be great if it's possible to add labs with predictive and descriptive models to this course (not only classification).

The case study used was difficult to understand.

The lab tutorial too were not detailed.

However the course is very interesting .

I really liked the course content. Although i would love see another case study added into the course for greater understanding

Very informative course with the exercises designed to cover complete data science methodology based on the Mr. John Rollins.

Examples shared to explain the methodology could have been a bit easy so every domain person can perceive it equally well.

the final assignment is too open-ended. no exact questions and answers. everything is left to understanding of your peers.

Methodology is clear. I liked the Python exercise with the recipes. I could see how it could apply to other industries.

Well-structured course with crystal clear explanations. Case study is intriguing. However lectures are still a bit dry.