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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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1826 - 1850 of 2,503 Reviews for Data Science Methodology

By Yifan H

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Aug 22, 2019

love the food recipe case! i am not familiar with clinical case but the food recipe case helped me learn the theory.

By David A

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Jul 15, 2019

A good introduction to the process a data science uses to answer complicated problems. I found it very interesting.

By Shubham V

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Sep 12, 2021

Content and learning is good, but you can improve quality of images used in videos. Sometimes text was not readable

By Jeevan K

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May 19, 2020

I found it difficult to understand the Data understanding step in the course.

Examples can be little in normal terms

By Amogh K

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Mar 24, 2020

The final assessment is very confusing for starters and needs to be more in line with the material actually taught.

By Praveen K

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Oct 13, 2019

This course should have been in the later stages. It is too early to understand all what the instructor has to say.

By Lilliana A

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Feb 2, 2022

Loved the course overall, only wish it had reference to further detail the theoretical base and see more examples.

By Kyle H

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Jan 24, 2020

A solid course that covers the fundamentals of the process a data scientist will go through to complete a project.

By Sherri S

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Nov 22, 2022

I know this is a management level course presented at a high level, but I was hoping for more projects/exercises.

By vince l

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Dec 31, 2019

A good overview on the Data Science Methodology. This course could be the launching pad for Data Science journey.

By Eric G

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Oct 9, 2019

A nice overview of methodology but at times it feels rushed. Assignments could do with a bit more rigour as well.

By Josimar K

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Jul 14, 2022

Great content. I learned more than I expected. tThe videos are great and the lab to practice are well elaborate.

By Korawan E

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Jun 4, 2020

This course is useful and very interesting but the contents of this course is formulated too hard to understand.

By Tim H

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Dec 21, 2022

This was a good introduction to data science methods. I appreciated the shortness of each video and assessment.

By Luie J

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Jan 24, 2021

A bit too fast. I think more case studies will help to understand the differences between the different stages.

By Bhuvana K

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Aug 5, 2022

the course provides more insights into data science methodology for resolving a problem with specific examples

By Mauricio F O M

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Oct 11, 2019

It needs to be more practical. A guideline telling what you really need to do inside each step would be nice.

By Christopher C

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Sep 1, 2019

Providing the slides for each of the lectures is advised as it helps students go back and review the content.

By Chonlapat S

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May 3, 2020

To little descriptive of each steps, too much focus on example which make it hard to apply to other problems

By Ranjeeth N

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Jul 21, 2019

Some times are not easily understood for beginners content needs improvement. There are some missing threads

By Partha S D

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Feb 18, 2019

Lectures were helpful and the content was great. It would be helpful if you guys can provide lecture slides.

By Andrigo M R

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May 22, 2020

It was a little difficult to understand the writing. Everything else was great. I'm learning a lot, thanks.

By Deleted A

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May 16, 2020

need more examples if possible,

the readmission example is not clear

the cuisine ingredients example is clear

By Vishakh V

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Aug 26, 2019

The video lecture sometimes feels too fast to follow as the content in the lectures are new to the student.

By Mark P

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Jul 25, 2019

The codes on the labs need updating. They don't generate the visualization necessary to reinforce learning.