Chevron Left
Back to Data Science Methodology

Learner Reviews & Feedback for Data Science Methodology by IBM

4.6
stars
20,486 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.

Filter by:

1851 - 1875 of 2,583 Reviews for Data Science Methodology

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 Abraham T

•

Aug 12, 2024

Me encanto este curso. Es un poco general pero aporta mucho conocimiento sobre que es una metodología y como te ayuda siendo un científico de datos.

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

By Soumyajit C

•

Nov 14, 2018

There is bug in the submission page of peer graded assignment. I had to submit thrice. Only a part of my answer was being uploaded after submission.

By Chris G

•

Feb 1, 2023

Good information but the first few sections were frustrating because you can't really answer questions about a complex model till you use it a bit

By Denis R

•

Dec 12, 2019

More time could have been spent on model evaluation as it is the most complex topic. Otherwise the class is very interresting and well structured.

By CINDY

•

Nov 4, 2018

An introduction class for those who never get in touch with Data Science, but for people who learnt this before, it is definitely a waste of time.

By asher b

•

Oct 11, 2018

Good overview of a "scientific method" applied to the field. this might be a better choice for the introductory course in the certificate program.

By Lane G

•

Nov 29, 2022

Overall a good beginning course for data science methodology. Some of the steps and processes could have been explained definitions/explanations.

By Md A I

•

May 22, 2019

Grading procedure is very weak and course has synchronization of lack of lab and theory. The lab seems very difficult with lots of python coding.

By Frederico C V

•

Oct 10, 2019

It could be much more interesting if we had the image of someone explaining, if we could see someone, that could show excitement on the subject.

By Sucheta

•

Aug 12, 2019

All steps of data science methodology are explained very well. Final assignment could have been more challenging (with some more quiz questions)

By Sonu K

•

Dec 19, 2022

This course is really very helpful for upcoming data scientists. i enjoyed a lot this course and i hope this will give me benefit in future.

By Niko Y

•

Jul 21, 2023

simple but not easy. But I would like it if they could include a written assignment in between the course too before the final assignment.

By Aditya M

•

Nov 12, 2020

In my opinion the first three courses of the IBM Data Science professional certificate can be neatly combined into an Introductory course.

By ABDELOUAHAB S

•

May 21, 2022

I really appreciate the methodology and how to use it

asort of check list at the end to emphazise the relevant point will be a great plus

By Naga M R D

•

Apr 19, 2018

Data science methodology is clearly explained with example. Voice in the video is bit, it could be improved. Great course for beginners.

By Sergio M

•

Nov 6, 2020

Very good examples to understand each phase of the methodology. Just include example for each type of approach would be five stars rate.

By Mikael B

•

Jan 2, 2020

This thing here is VITAL! I would loved this to be bit more hands on. But i guess learned will be applied more closely in next courses.

By John F

•

Dec 1, 2024

Solid course, would be great if the embedded labs (web based Jupyterlite) could be accessed separately for use as reference material.

By Hong W

•

Dec 4, 2019

A very good framework to guide the analysis. I think it's better to put it just after the orientation session while before the tool.

By Anuj M

•

Jul 8, 2019

Hi I found this course useful though there can be better example than food and linking of python at lab rite away was more confusing

By Kristin R

•

Dec 13, 2018

This could've been condensed down immensely, but I suppose it's something you deal with when sorting through data for data science.

By Hanieh I

•

May 5, 2020

The course was very informative I just wish it went into a little more detail of the statistical tests used in the methodologies.

By Liza V

•

Jan 27, 2020

It's quite clear and interesting course. What lack is a reference to additional reading to give more overview about the subject.