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Learner Reviews & Feedback for Data Science Methodology by IBM

4.6
stars
20,942 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

NN

Jul 6, 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.

JG

Nov 29, 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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751 - 775 of 2,651 Reviews for Data Science Methodology

By Arun N

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Feb 16, 2020

This course helped me in writing the approach note for real-life project

By Ravi N

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Jan 2, 2020

I was a bit distracted... but reviews helped... and thanks for extending

By Shaheryar

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Sep 10, 2019

One of the best courses I currently had. Explains things in good manner.

By Rafael D B

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Jun 5, 2019

This course was better than the last, clearer and with better exercises.

By Overs M

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Oct 13, 2022

An exciting , educative course in the professional data science series

By JOHN D K F

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Jul 26, 2022

The course is extremely beneficial to one's career and personal growth.

By Dickson M K

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Oct 4, 2021

Organized, well-articulated and informative. The instructor was amazing

By Juan A M C

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Sep 3, 2021

This course helps to understand all the methodology behind data science

By John L

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Jan 7, 2021

Excellent input, It will be very helpful for us students in the future.

By Dheeraj k S

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Nov 5, 2020

A clear step-by-step guide to approach a problem to solution with Data.

By Ankur S

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Apr 5, 2020

Very nice course to explain all the phases of data science methodology.

By Piotr M

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Feb 24, 2020

A short course to give basic understanding of data science methodology.

By abhishek p

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Oct 21, 2019

this is really helpful to understand the concepts of data science cycle

By Cristian O R R

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Oct 5, 2019

It's great that you see a study case when you're learning something new

By Winston C

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Sep 4, 2019

i like the course but i do think you need more detailed demonstrations.

By Emi H

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Jun 6, 2019

It is a good course for gaining foundational knowledge in data science.

By Vinay K M

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May 29, 2019

Course will explain in details of reporting and how to collect the data

By Chris B

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Apr 10, 2022

Great description of the CRISP-DM model and what occurs in each stage.

By Subhadip P

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Jan 10, 2022

Excellent Course for beginners. Especially case studies are brilliant.

By LIAQUAT A

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Oct 20, 2021

It was a very useful course. It was well organized and well presented.

By Iyanna W P

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Aug 21, 2021

Excellent overview of the methodology behind the data science process.

By Brian O

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Aug 3, 2020

Very good. Interesting case study along the whole length of the course

By Ray F

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Jul 24, 2020

Good overview on how Data Science is applied to business applications.

By rohan j

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Jul 14, 2020

This Course was great for Acknowledgment Of Data Science Methodology.