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Learner Reviews & Feedback for Data Science Methodology by IBM

4.6
stars
20,492 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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2376 - 2400 of 2,583 Reviews for Data Science Methodology

By Harshit k s

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Jun 12, 2020

The case study was not that good, some good examples need to be added.

By Ariel E

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Jan 31, 2019

I'd like to see exercises where we can practice the methodology phases

By Deshan G

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Jun 21, 2023

This course was a bit hard and the explanations were a bit difficult

By Akalah F

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Oct 7, 2019

the video lectures was really fast making it difficult to understand

By Philipp K

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Jun 12, 2019

too much information on slides. Use more pictures for visualization.

By Hareesh T

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Jan 31, 2019

An introductory overview of what Data Science actually is meant for.

By Vasudev S

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Jun 7, 2020

Make this course more intuitive rather than being just all theory.

By Gokul N

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Apr 18, 2020

Too theortical course ,could have an eaiser case study to explain

By Mohammad Q

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Aug 21, 2019

Good Methodolgy but I feel like I need more explaination about it

By Paren A

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Mar 9, 2019

Nice overview, but brushed over far too many topics very briefly.

By Harishankar

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Apr 11, 2020

The video narration is so boxy type, and need to be interactive.

By Clifton W

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Sep 4, 2023

The case study was difficult to follow and understand at times.

By Michael O

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Apr 15, 2021

A good introduction to some of the basic ideas of data science.

By Wali A

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May 27, 2023

A little boring in begining of course! but intresting at last

By Amanda C

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Dec 18, 2019

This course teaches memorization of a proprietary flow chart.

By Sourabh S

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May 9, 2020

Very Theoritical Course, and honestly a bit boring as well.

By Avinash K

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Feb 19, 2020

Bit confusing - especially the analytical approach chapter.

By Leon W

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Apr 4, 2022

Good structure

I think I spotted 1 content-related mistake

By Veera v p p P

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Sep 8, 2020

Modelling and Evaluation needs more examples for beginners

By hassan a

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May 17, 2020

Course is more on theory but less on practical approach

By Chris L

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Oct 15, 2019

common sense is rated as professional in this course.

By Aleix C T

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Jul 17, 2019

good content, surprisingly weak delivery and teching

By Stuart B

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Jul 28, 2022

technical difficulties with the ungraded workbook

By Leandro S

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May 8, 2020

More deep treatment for some concepts are necesary

By V S G

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Apr 12, 2020

More real-time cases can help to understand better