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Learner Reviews & Feedback for Data Science Methodology by IBM

4.6
stars
20,486 ratings

About the Course

If there is a shortcut to becoming a Data Scientist, then learning to think and work like a successful Data Scientist is it. In this course, you will learn and then apply this methodology that you can use to tackle any Data Science scenario. You’ll explore two notable data science methodologies, Foundational Data Science Methodology, and the six-stage CRISP-DM data science methodology, and learn how to apply these data science methodologies. Most established data scientists follow these or similar methodologies for solving data science problems. Begin by learning about forming the business/research problem Learn how data scientists obtain, prepare, and analyze data. Discover how applying data science methodology practices helps ensure that the data used for problem-solving is relevant and properly manipulated to address the question. Next, learn about building the data model, deploying that model, data storytelling, and obtaining feedback You’ll think like a data scientist and develop your data science methodology skills using a real-world inspired scenario through progressive labs hosted within Jupyter Notebooks and using Python....

Top reviews

AG

May 13, 2019

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 :)

JM

Feb 26, 2020

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.

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2026 - 2050 of 2,583 Reviews for Data Science Methodology

By Ridhi S

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May 13, 2020

It was a good one, but try to take a simpler case study material.

By Ravindra D

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Nov 13, 2019

Good course primary focus on methodology (a theoretical approach)

By Nicklas N

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Jan 17, 2019

A good overview of the scientific method applied to data science.

By NARENDRA E

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Apr 13, 2022

The course is covering all the phases of DataScience Methodology

By Russell K

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Feb 23, 2020

peer graded assignment was graded unfairly for first submission.

By Siwei L

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Jan 8, 2020

Case of heart failure not common enough for a easy understanding

By christopher r n

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Jun 13, 2020

the github was hard to follow and the was some technical issues

By yonghui f

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Feb 28, 2020

Kind of basic knowledge, give you a thought about data science.

By Beast C R

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Sep 17, 2019

Good information. More interaction and less video would be nice

By Hamza Z A

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Nov 22, 2018

A bit more descriptive videos could have made this even better!

By Ibraheem K

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Jan 8, 2022

Easy course, prepares you to have a clear mind about the topic

By Ritvik S

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Sep 1, 2020

Very good explanations and well-guided throughout the course.

By Nagarjuna K

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May 29, 2019

very good support to Coursera IBM Data Science certification.

By Muhammad E N A A

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Sep 10, 2023

I'm having trouble with the language, there's no translation

By ROBERT R

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Mar 1, 2021

Tough, for my first set of data science courses, but doable.

By 郑上

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Apr 10, 2020

the final exam is not easy,I uploaded it for three times....

By Nirav

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Jun 7, 2019

A common example could be easier to understand for everyone.

By Viet H N

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Mar 27, 2020

The example about medical in videos is hard to understand.

By Jayesh M

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Aug 16, 2019

Use cases could be given from different industry as well.

By Vivek N

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Jul 28, 2019

Language of Presentation was very difficult to understand

By Sibusiso T

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Dec 5, 2019

We can go deeper with more examples and a sample report.

By Sathiya P

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Aug 3, 2019

It was good, but it could have been made slightly simple

By Mohitkumar R

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Nov 16, 2018

Great knowledge to methdology and data science thinking.

By Maxim V

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Oct 16, 2018

actually not useful for anyone who did research projects

By Yugal B M

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Apr 26, 2020

The case study used was little bit tough to understand.