Avis et commentaires pour d'étudiants pour Data Science Methodology par IBM

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.

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.

Excellent Course! Very nicely designed and delivered. The Data Science course is easy to grasp and made very interesting delivery. I am excited to learn more.

It is helpful for me to learn the process how to do with data science methodology.

Thank you for your great teaching and quiz to help me improve my new skills.

Excellent course with tons of great information. It provides a great step-by-step review of the methodology while still keeping things somewhat challenging.

Change my perspective towards the data science.

Before starting to step in towards data science every individual should understand its methodology completely.

Awesome course! Thanks for putting together this wonderful course. Well prepared labs, and some informative discussions in the forum are the additional pros.

Didactic course, supported with the assignment to conclude, gives you an understanding of the data science methodology, meticulously. I'll give it a 5-star!!

It was a challenge for me to get on with the tasks and especially to understand all the concepts. But I believe it will be of great value to my profession.

This course with you a good base to build your career as a data scientist. A follow a methodology is a must in order to success in every job. Nice course!

It was a short course focused mainly on the steps of a data science procedure. All the 9 courses of IBM Data Science Professional Certificate is valuable.

Very interesting course with lots of case study examples, with great lab works. Course gives opportunity to understand the methodology of the Data Science