Learner Reviews & Feedback for Data Science Methodology by IBM

4.6

stars

20,981 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

Jun 15, 2020

Great Course. It was a simple course and to the point. It explained the concepts perfectly for future advancement. I think the theory in here could be applied to any problem data science or not

May 16, 2021

A bit more complex than what I would have hoped, but the material is still digestible. I think this course could be improve if the lecturer slow down a bit and spend more time on each topic

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2651 - 2661 of 2,661 Reviews for Data Science Methodology

By Melvin C

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Mar 21, 2025

Final exam not showing for me

By maazin k

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May 16, 2020

Not good.Not worth at all.

By IQBAL H

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Apr 27, 2022

cant generate certificate

By Nicholas J

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Jan 27, 2020

Not very useful at all

By Avi

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Nov 5, 2019

not stimulating at all

By RABİA K

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Oct 19, 2023

#zionistterrorism

By Abdurrachman M

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Apr 20, 2018

Not interesting

By Naga s T

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Feb 21, 2023

not impressive

By Saptashwa B (

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Apr 8, 2019

Useless Course

By Jean-Yves R

•

Oct 29, 2021

Really bad.

By Boru R

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Sep 5, 2020

Useless