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

17,893 ratings
2,214 reviews

About the Course

Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don't have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand. This course has one purpose, and that 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 tackling a data science problem. - The major steps involved in practicing data science, from forming a concrete business or research problem, to collecting and analyzing data, to building a model, and understanding the feedback after model deployment. - How data scientists think!...

Top reviews


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!


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 :)

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1676 - 1700 of 2,222 Reviews for Data Science Methodology

By Long N K H

May 31, 2020

This incredible course provides me the methods that I can apply to real world problems

By Jude S D S

May 8, 2020

The last peer-graded assignment is not a good idea...should be reviewed by teachers.

By Luis C M

Mar 19, 2020

I would like to have more investigation and exercises than watching a lot of videos

By Language L

Feb 21, 2020

Good lesson, but some of the explanations could have been better or maybe less dry.

By Maksim M

Mar 13, 2019

I got a general idea of Data Science methodology and the flow of a research project

By Rithwik P

Apr 26, 2020

I feel it could be a little more simplified near the modelling and evaluation bits

By juadolfob

Mar 31, 2020

Too many videos, I would appreciate more lectures.

The labs are really great !!! :)

By Vaibhav A

Apr 6, 2020

Didn't find enough explanation on Machine Learning Model applied during modeling.

By Luis O L E F

Nov 5, 2019

Nice introductory course for the basic steps to follow in a data science project.

By Mike

Jan 29, 2019

Very good course. The example is a bit odd one - or we could say the explanation.

By Keno K

May 3, 2021

Good course on methodology, would prefer even more exercises like the final one.

By Mohammad S A

May 3, 2019

I think the examples would be more precise to understand the methodology better.

By Jana A

Mar 22, 2022

I love how it's delivered the aspects of the methodology in a simply clear way.

By David C

Mar 13, 2022

good, straightforward presentation of a solid methodology with simple testing.

By Mariya M

Feb 23, 2021

It may include a bit more datails and excercises, but overall very good course.

By Naveen S

Apr 6, 2020

This course should be in more details. More practical is required for hands on.

By Nikhil C C

Oct 17, 2019

Case study was boring and cannot understand without basic idea about the issue.

By Diganta D

Mar 28, 2019

One of the most important course to do in data science and also a valuable one.

By Ray

Feb 29, 2020

Great course, could use further explanation of some of the statistical methods

By Ankita S

Feb 20, 2019

One of the main module to understand the data science process. Great content!!


Oct 15, 2018

Could you please consider providing the slides it would be awesome, thank you.

By Ajeet K

Jun 20, 2020

This course very useful for how to use data for a particular business problem

By Julia N

Jul 1, 2019

Peer-graded system is not suitable for this course. Or it should be improved.

By Julien P

Jan 12, 2020

Good for beginners in data science. Optional if you are already experienced.