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Learner Reviews & Feedback for Data Science Methodology by IBM

4.6
stars
20,554 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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2201 - 2225 of 2,592 Reviews for Data Science Methodology

By Abdelhamid G

•

Dec 24, 2019

very good

By Koyya S

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Mar 4, 2019

Thnakyou.

By ShanQiu

•

May 11, 2019

Not bad~

By raul

•

Aug 1, 2024

Nice!

By Amarzaya

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Mar 4, 2020

liked

By Emmanuel O

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Jan 19, 2020

Great

By Om D G

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Jan 15, 2025

nice

By Oluwamakinde I

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Oct 6, 2024

good

By Mon P

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Apr 8, 2024

good

By GOURAB G

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Aug 27, 2023

good

By Mohammad A

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Nov 13, 2022

good

By Lizeth C

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May 1, 2022

good

By Raja M N

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Jul 7, 2021

good

By Muhammad S A

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Oct 14, 2020

good

By Shone G

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Jul 22, 2020

good

By Pagadala G s

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May 2, 2020

Good

By G V

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Mar 10, 2020

good

By Satishkumar M

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Jan 4, 2020

G

o

o

d

By Akhil K

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May 14, 2019

Good

By S M

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Jun 11, 2019

4.5

By Shruti R

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Apr 28, 2020

NA

By Adil S

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Jan 27, 2019

AS

By Nestor R V M

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Nov 12, 2018

:)

By Daniel L A

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Jun 22, 2019

-

By Andrei P

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Apr 13, 2019

The information was somewhat confusing at times and it was kinda hard to follow the lectures even though the information provided was quite basic nad not too complex. I guess the problem with this course is the way the information presented and the overall flow of the presentation.

Also the labs, they confused me even more because we get presented with some amount of code which was not covered before. You are supposed to be able to complete this course without any coding, but you get all this unnecessary code, which doesn't even matter in the end but adds to the confusion and makes the lab harder to follow. I think it would be better to get rid of the code, or to include these labs after the python course, so the students can easily follow what's actually going on in the labs.

As i figured from the discussion section there is a number of students that were a bit confused about what actually should be in the final assignment (myself included). I had to rewatch all of the videos and revisit all of the labs just to get vague understanding of what needs to be done.

I am still unsure if what i wrote in the final assignment was even 100% correct (even though i got the top score), simply because these assignments are being judged by peers, not mentors.