Learner Reviews & Feedback for Data Science Methodology by IBM

4.6

stars

21,001 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

Jul 7, 2019

I like the way they provide sample with food preparation on each of the stage of data science methodology. Need to give more sample for the study case to give more insight and understanding.

Nov 30, 2019

This was a clear and concise overview of the methodology and using the case study really helped (although sometimes it got a bit advanced considering this comes before actually learning models).

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2076 - 2100 of 2,669 Reviews for Data Science Methodology

By Lalit K

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Aug 2, 2022

Course is good but the video in the course could be more elaborative .

By Dipak J

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Apr 25, 2020

Scope for improving Peer Assignment .

Do not see paste and paste twice

By Ala'a N E

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Feb 20, 2019

I had a problem in the case study, it was difficult to understand it .

By Angus C

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Jul 5, 2023

The content is interesting, but can be more interactive in the video

By Ahmed E

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Jan 3, 2021

The course is amazing.

But I didn't like that the course is narrated.

By Mek T

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Jun 4, 2020

Good course but a little short in explanation of some of the topics.

By Aditya S

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Feb 26, 2020

Good course to know the steps for carrying out Data Science projects

By Felipe J

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Feb 26, 2019

Describe very good the phases to resolv a problen using data sciense

By MANIKANDAN T

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Jul 6, 2020

Gives good understanding of step by step processes in Data science.

By Esau H H

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Sep 16, 2019

To the point and the case study really helped get the point across.

By Amit S

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Jul 1, 2019

This course gave me good insight about the data science methodology

By Shuyuan C

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Jun 21, 2019

A good introduction to get useful skills for data analysis process.

By Pragya A

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Jun 17, 2019

more explanation is needed.....example of hospital is not so easy.

By AYUSH A

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Jun 6, 2019

case study in videos is less understandable but in ungraded notes.

By Matt A

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Apr 2, 2019

Very comprehensive view of methodology with real-world case study.

By ROBERTO I D L R C

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May 23, 2021

I have a bigges scenario of how to manage a Data Science project.

By Jeroen O

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Dec 15, 2020

Good course......it provides a good intro to the CRISP Framework.

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 14, 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 24, 2020

peer graded assignment was graded unfairly for first submission.

By Siwei L

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Jan 9, 2020

Case of heart failure not common enough for a easy understanding

By christopher r n

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Jun 14, 2020

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

By yonghui f

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Feb 29, 2020

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