This is one of the fantastic course in data science. I enjoyed a lot learning through this course. It had explained nicely, various data science methodologies with case studies.

The course is well done. In particular I really appreciated the laboratories, which I really believe help to put in practice and understand what has been taught during classes.

As an engineer, i know the importance of methodology not only on data science field, but on every part of the life. This course covers every aspect of data science methodology.

I think this should be the second course to get a Data Science's big picture of the process it involves and then get more to the especific tools such as the open source ones.

Videos and material are excellent! Manageable and understandable course giving good overview with practical and clearly defined steps towards solving data science problems.

Brilliant course. But one problem that i faced was the example of American health system, it was very difficult to follow as i didnt have any experience of knowing about it.

I have not seen any other course which details the methodology in this manner. Definetely took home some very important points and will be using it in my projects as well.

Really good content. It is a bit theoretical but it helps you get a clear understanding of what the different steps and actions are when working in a data science project.

Thank you,

this course was very interesting and thoroughly explained.

The food metaphor was very helpful and really made the difference to understand it all.

Thanks, cheers!

I learned a lot about it. As I never seen such content since I have started using and practicing the data science. So, I like the lectures And I really got something new.

I loved this class! What really helped was having a hypothetical case study to demonstrate how the data science methodology is applied. I also really enjoyed the labs!

Very structured outlook on how to tackle a data science project. The case study was very helpful and definitely contributed to clarify concepts presented in each stage.

This is the most vital course in learning to think as a data scientist. I will never forget this course, It is the core system of what data scientists do! Great course!

Very interesting and easy to understand Course than any other course here. Thanks to Coursera for making us part of the IBM Family. I am proud to be part of this Family

This was a very good introductory course. I have been a data scientist for years now and self-trained. This was a great way to have the approach for what I do codified.

The material is greatly informative and clearly explained. I'd some trouble understanding the case study. A simpler one would be really entertained and helpful. Thanks.

Very Practical. The methodology presented can be immediately applied in many situations (even not related to data science). Everything well explained and exemplified.

This course explained how to deal with the process of dealing with data science problems and determined the questions which i must answer to succed in solving problem

Nice course I highly recommend everyone to take this course as this course will teach you what are the steps that we need to take in order to solve business problem.

its an amazing course to understand the flow and structure of being a data scientist. you'll love going through this course and would definitely learn a lot from it.

Simple and accurate description of the Methodology behind Data Science, and more importantly the exercises are created to implement this learning in a precise manner

Great course, would be even more useful if additional reading materials were given. It requires a lot of self research and reading to understand the concepts best !

The content covered on this module is sufficient for a beginner to get and idea of what Data Science Methodology is and how to implement it in real world scenarios.

Completely helps you understand the methodology employed by John Rollins (IBM), takes the help of a case study to show you how one can practically apply the same.

Course content is complete and to the point, the explanations and examples given are enough to expose the concept and then you can explore further on each topic.