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Learner Reviews & Feedback for Data Science Methodology by IBM Skills Network

18,815 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. Most of the established data scientists follow a similar methodology for solving Data Science problems. In this course you will learn and then apply this methodology that can be used to tackle any Data Science scenario. The purpose of this course is to share a methodology that can be used within data science, to ensure that the data used in problem solving is relevant and properly manipulated to address the question at hand. Accordingly, in this course, you will learn: - The major steps involved in practicing data science - Forming a business/research problem, collecting, preparing & analyzing data, building a model, deploying a model and understanding the importance of feedback - Apply the 6 stages of the CRISP-DM methodology, the most popular methodology for Data Science and Data Mining problems - How data scientists think! To apply the methodology, you will work on a real-world inspired scenario and work with Jupyter Notebooks using Python to develop hands-on experience....

Top reviews


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 :)


Jun 18, 2021

Very interesting course. It shed a light on what the structured approach really is. It's worth to pause for a moment with every step of the methodology and think how to apply it in real life. Thanks!

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2151 - 2175 of 2,347 Reviews for Data Science Methodology

By Hassan B

Aug 20, 2019

It's good course but still need more explanations and examples to be clearer.

By amir s

Jun 7, 2019

The assignment is not very clear. The example had better to be more iterative

By Joaquin M S

Mar 1, 2023

It seemed a bit basic, so there´s a lot the student has to dig by themselves


Nov 1, 2018

a slight bit more technical than the previous two courses. Getting there ..

By Ulvi S

Jul 24, 2021

It could be prepared much easier. It is hard to understand for non-natives

By Hiral M

May 1, 2020

Examples and case study in video of CHF was a bit difficult to understand.

By Minsung K

Nov 1, 2021

Personally, very dull course material; please generate me a certificate.

By Yadder A

Dec 7, 2019

I think that should have more information. And quizzes should be harder.

By Taimore I A

Jul 30, 2019

Case study should be covered in more detail. The other content is good.

By Nidhi K

Jun 13, 2022

This module would be more beneficial after learning basic ML concepts.

By Harshit k s

Jun 12, 2020

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

By Ariel E

Jan 31, 2019

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

By Fabrice A

Oct 7, 2019

the video lectures was really fast making it difficult to understand

By Philipp K

Jun 12, 2019

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

By Hareesh T

Jan 31, 2019

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

By Vasudev S

Jun 7, 2020

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

By Gokul N

Apr 18, 2020

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

By Mohammad Q

Aug 21, 2019

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

By Paren A

Mar 9, 2019

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

By Harishankar

Apr 11, 2020

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

By Michael O

Apr 15, 2021

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

By Amanda C

Dec 18, 2019

This course teaches memorization of a proprietary flow chart.

By Sourabh S

May 9, 2020

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

By Avinash K

Feb 19, 2020

Bit confusing - especially the analytical approach chapter.

By Leon W

Apr 4, 2022

Good structure

I think I spotted 1 content-related mistake