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Learner Reviews & Feedback for Data Science Methodology by IBM

4.6
stars
19,899 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.

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1801 - 1825 of 2,503 Reviews for Data Science Methodology

By Aditya M

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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

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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

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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

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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

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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 Hong W

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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

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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

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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

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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

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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.

By Pavel N

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Nov 21, 2021

It would be great if it's possible to add labs with predictive and descriptive models to this course (not only classification).

By J. O M

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Mar 2, 2020

The case study used was difficult to understand.

The lab tutorial too were not detailed.

However the course is very interesting .

By Anup J M

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Sep 19, 2019

I really liked the course content. Although i would love see another case study added into the course for greater understanding

By Imran R

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Jan 7, 2019

Very informative course with the exercises designed to cover complete data science methodology based on the Mr. John Rollins.

By Sharvari U

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Oct 6, 2019

Examples shared to explain the methodology could have been a bit easy so every domain person can perceive it equally well.

By Serdar M

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Oct 25, 2018

the final assignment is too open-ended. no exact questions and answers. everything is left to understanding of your peers.

By Maria N W

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Jun 22, 2021

Methodology is clear. I liked the Python exercise with the recipes. I could see how it could apply to other industries.

By Zezhou J

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Sep 27, 2018

Well-structured course with crystal clear explanations. Case study is intriguing. However lectures are still a bit dry.

By Mohammad R

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Aug 28, 2022

This course wouldn't be helpful at all if it wasn't in the data science program. This couldn't be an individual course

By Yash T

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Oct 28, 2021

The example of Congestive Heart Failure given in video to explain data science methodology is difficult to understand.

By Yoshihide J S

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Jan 8, 2021

I feel we need slightly more case study, not enough case study example! So, understanding the meaning "methodology".

By Nikhil J

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Jul 4, 2020

It gave a nice overview of how things flow in a data scientist mind. Provides a framework to think approach problems.

By Stanley Y

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Nov 29, 2019

Peer-reviewed exercises often result in inconsistent feedback! The course requires a more rigorous method of grading.

By Emilio B

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May 7, 2020

Buen curso aunque a mi parecer un poco monótono y repetitivo a veces. No tenía muy claras las explicaciones a veces.

By shibu p

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Sep 24, 2019

I learned a lot on Data science methodology. Now i know how data scientist thing and work. It was a good experience.