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

17,898 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


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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1926 - 1950 of 2,222 Reviews for Data Science Methodology

By Ra G

Jul 1, 2022

Very nice course, but I have a few points -

1. As this module is a part of a single course. It would be much more better if the python codes remain same in all the modules. for eg. in one module for splitting datasets we use sklearn train_test_split, but in another we use numpy.

2. As good we explain the methodology in this course, python codes are not explained properly.

By Morgane B

Aug 23, 2020

Ce cours présente quelques méthodes d'analyse, mais elles ne sont pas assez structurées. Une présentation plus exhaustive des méthodes avec des exemples, voire une nomenclature pourraient être plus utiles. Le cours gagnerait en qualité s'il donnait un schéma par type de données et méthodologie de traitement conseillée avec ensuite les outils techniques recommandés.

By Evgeniy A

May 22, 2022

This course need to be more informative and give more details about each step of the DS Methodology. Maybe more info on models - what models are there, how they can be classified. More info about types of the analysis. The corresponding literature recommendation would also be awesome. Overall - good course to give you an overiew on Data Science Methodology.

By Hadi S A

Jun 26, 2019

Its an amazing course to give you an introduction to Data Science Methodology. But the case chosen was a hard case to understand specially if someone is a beginner in statistics and not into the medical field. I wasn't the only one who got confused while using the methodology on the case shown. Hopefully, a simpler case gets introduced in future.

By Dita A

Mar 4, 2019

The course is good but the way the example is explained is a bit confusing, especially the when jumping from study content/material to the example.

The peer to peer review for the final assignment is veeeerrryyy subjective. I had to submit 3 times (with little to no change on my answer) in order to pass. Good luck on getting a nice reviewer! :)

By Brandon B

Apr 29, 2020

CONS: I would really prefer more interactive lectures. The lectures tended to be boring and monotone. Also the case study content many times was difficult to grasp because it is very specific to hospital field.

PROS: The material covered is quite beneficial in understanding the overall data science process. It is a nice summary.

By Tim P

Apr 23, 2020

I thought the course was pretty thorough. Differences between AI automation and data science problem solving is not really explored. Also the main case study was a little out of date and not very well explained. I thought it was a course worth taking as the material around the earlier parts of the methodology were really good.

By Abraham Z

Jan 3, 2020

IBM Developer Skills Network was have connection issues during the lessons. I worked on this course at several different locations on two different PC environments. One PC was a corporate controlled windows system, and the other was personal windows system. These connection issues distracted from the course content.

By Rakshit K

Sep 10, 2018

If you could have explained the terms related to machine learning more and if you could have spend more time on understanding the Actual problem of the case study and then slowly built up the solution it would have been great course. I loved the organization of course but not the flow of the course. Thank You.

By Muhammad U T

May 30, 2019

It provides a satisfactory overview of the data Science methodology, but the slides and the videos does not suffice the needs to fully understand the concepts and the Labs. Supplementary readings for this course are MANDATORY to understand and fill the knowledge gaps for several topics named in the videos.

By Tom H A L

Jan 30, 2020

This course would benefit from more real life examples, and more time spent on an overview of the methodology prior to looking in depth. How the stages would be applied is not explained very clearly. Having completed this course, I am not completely confident in my knowledge of the contents.

By Marcio A

Sep 29, 2020

The course is very good. Using a 'case' is helpful to the process. The material presented is also very good, however, would be goog if it was avaliable for the students, even in PDF format. The transcriptions itself are not enough and I was expecting more from Coursera and IBM .

By Esteban P

Jul 19, 2019

I think that they should define more the specific concepts of all the states of the methodology, and then make references to "hypothetical" cases. Personally, I lost more trying to understand the examples and I had to go to find more specific information in other sources.

By Nigel D

Jan 26, 2020

I really enjoyed the information in the course. Despite having all the information necessary to pass, I do not feel like the course went into enough detail on some of the topics in order to make them understandable. I think this course should be more in-depth than it is.

By Nick L

Sep 9, 2020

Although the course does provide a high-level overview of the IBM Data Science Methodology, I would say it does so at a very basic level that does not really help you prepare for any real-world on-the-job application. I can only hope the coming modules go in more depth.

By Ogbonna O

May 17, 2020

The course was good but I feel the materials need to be updated. I do not think the videos get down to the nitty-gritty of the concepts. To complete this course, I still had to use external content a lot more than I did in previous courses to get proper understanding.

By Kazi M R

Apr 26, 2020

The concepts discussed in the video lectures are not clear enough. Also the case/example used in the video lectures have complicated terms and requires some subject matter knowledge. However, the labs are very well designed which helped in the understanding process.

By Patrice J E

Apr 5, 2020

There were issues with Jypter notebook not working. I also felt for some of the steps such as Data Understanding, Data Preparation etc the descriptions of the stages were too similar which let to confusion. See Week 2 Forum messages. Overall i enjoyed it nonetheless

By Mak C Y

Apr 26, 2019

Grateful if more explanation or more cases can be given. Also, I found that the final assignment has a mistake, making the total available scores changed from 10 to 9, which force us to make a "perfect answer" to get almost a full mark (the passing mark is 8 marks).

By Firda S

Jan 26, 2020

I think the case study is too hard to understand. The analogy using cooking it's good, however, the case study using hospital problem it's really hard for me to understand. Maybe it could improve if it's using like general case study that everyone would understand.

By Marvin R

May 19, 2020

The examples were confusing at some point. The videos could've expanded the concepts more so that the differences between each stage of the Data Science Methodology becomes clearer. The case study in the video is also confusing for someone in a non-medical field.

By Ellen H

Feb 17, 2020

Pretty good course, but could have been a little more challenging. I'm glad I learned the process, but I'm ready for some more hands-on work. This was getting close- I think the final projects, especially for week 3, were good practice to apply what I learned.

By Suyog J

Oct 9, 2019

Appreciate the content so far. This can be though made more in-depth when it comes to hands on. Including graded level hands on practice can enhance the learning experience the students get from this course.

Thanks for enabling us with all through the course.

By Chaojie W

Oct 26, 2019

I understand that this video want to give a full image of Data Science. But its case study including too much low-frequency vocabulary / terminology, which is an obstacle to beginner. And some reading material 's exercise is not very necessary...

By Alina T

Jun 27, 2019

I found this course to be a little bit too vague and theoretical, and hence, difficult to understand sometimes. I personally prefer to study and work with hands-on and applied aspects of Data Science instead of theory and vague definitions.