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

18,828 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


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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1651 - 1675 of 2,347 Reviews for Data Science Methodology

By Christoph W

Feb 28, 2021

Quite nice, really lets one follow the methodology - good mixture of videos, labs, tests. Final assignment is great to develop a full concept for a specific problem.

By Charles K F

Apr 26, 2020

The content needs to be updated and better align with the lab work. I was expecting more functional lab tool examples like RStudio, Zeppelin, and Jupyter Notebooks.

By Rommy L

Feb 20, 2023

This course assumes that the taker has taken statistics and remembers a variety of terminology from that course. A refresher/terminology reference would be helpful.

By Oliver F

May 4, 2020

I 've learn a lot from the good course and resource, but too many medical terminology make the video difficult to understand for a non-native English speak learner.

By Rivers L

May 24, 2020

The assessment and the review method for this course need to be improved. I would suggest the passing rate would need at least three person review instead of one.


Mar 10, 2020

The lab often dose not work properly, and the vedio of lecture is a little bit confusing to understand, it should be well oganised. The course is helpful anyway.

By Heinz D

Jan 8, 2021

Good lectures on the data science methodology including an understandable case study. The peer review procedure is a bit strange, but it worked out at the end.

By Gemeng Z

Apr 16, 2020

The course introduces some basic ideas of the methodology practice of data science, which gives a general picture of the typical workflow as a data sciencetist

By Joshua E U

Dec 2, 2019

This course was indeed very helpful as it help me understand the need for data science methodology as i build up my career as a data scientist in data science.

By Matthew A

Apr 22, 2019

Overall a solid course with a good overview of many data science concepts. Some of the exercises need to be updated to reflect the current IBM Cloud tooling.

By spandana k

Apr 2, 2021

I found this course a bit difficult to understand and had to view the videos multiple times to get clarity, probably due to lack of knowledge in statistics,

By Mario E G P

Jul 31, 2019

The content of the course is good, but how the videos are made produce me sleep, because the content is not expalined in a natural way, but it is only read.

By Nora S I

Dec 18, 2018

Quite complete. I recommend it. It didn't get 5 stars, because too many concepts were just brushed over, but it is an excellent review of how to handle data

By Aiman A A G

Mar 1, 2022

It would be even better if we are provided with the slides to review by ourselves before the final exam instead of needing to go through the videos again.

By Gulnara Z K

Aug 30, 2021

Very well designed! Some of the best courses! Good videos with illustrative images and quality sound. Would be nice to get some help with the lab exercises

By Joana M D V P M S

Jun 3, 2020

Great content and clearly explained. I would just add more practical exercises to consolidate all the information provided. But I really enjoyed. Thank you

By Sai P B

Jul 15, 2019

This gives a basic knowledge of Data Science and explains neatly in every steps. Appreciate your efforts in putting this course in neat and expressive way.

By Rajesh W

Sep 10, 2018

Some concepts are difficult to understand, probably because I am hearing them for the first time. Hopefully, next section of the courses will address this.

By Vijayalakshmi K

Jun 26, 2019

Great course with lot of good information.. but a bit over the head stuff for non technical people due to all the Python language included in the course.

By Anuar M

Feb 26, 2020

Good overview of the data science methodology. However, to fully understand the topic, need to do more practices and hand-on on the real world project.

By Michael P

Nov 16, 2018

Teaches you how to think like a data scientist within the business context. Instructor could do a better job at explaining things the quiz tests you on.

By Koji J

Dec 28, 2020

Very structured content which is easy to understand. A case sudty with less medical terminology would be easier to understand for non-native speakers.


Mar 23, 2020

The case study used in the course was too complex to understand, choosing different case study to explain the concept is more beneficial for students.

By Scott G

Sep 17, 2022

Generally very good content. I would like to have learned more about the various analytic approaches with more examples of when each is appropriate.

By Roman I

Sep 6, 2022

Good overview. However, a simpler example rather than medical could be used. The medical terms are difficult to understand for a non-native speaker