This course is nearly PERFECT. In DS, it's really important to take step-by-step methodological approach and this course contains everything in it. Highly recommended :)

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

A very entertaining and interesting course, the use of metaphor, as well as the case study, helps a lot to understand the syllabus of the course, totally recomeded.

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.

I had fun with the final assignment. Its like a real taste of how you would apply data science methodologies to your reports. it was almost like a research paper!

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.

Even though I was not familiar with most of the Python code in this course (which is covered in other courses), it provided a great insight into the methodology.

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.

Great course! I really appreciate all the information shared. It would be even more amazing if we exmained some data analysis reports provided by some companies.

The methodology presented in this course for Data Science is very good logical step-by-step approach from understanding the problem to modeling and feedback.

This course is pretty short, yet it really well summarizes the key aspects of Data Scientist's work. Furthermore, the last exercise is pretty well and demanding.

This course has really given me a clear view of the whole conceptual process of a data science project. The basics have been quite clear and easy to understand.

I have learned a lot from this course even though it was tough to understand some concepts. The course is giving me motivation to study further on Data Science.

Definitely a must for beginners of Data Science (like myself). Gives a good overview of how all the major working parts of a Data Science project come together.