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Learner Reviews & Feedback for Data Science Methodology by IBM

4.6
stars
20,367 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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2276 - 2300 of 2,569 Reviews for Data Science Methodology

By Prabir C

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Sep 11, 2019

very theoretical topic and hard to follow with case study give, The final assignment is also very unclear on what to expect. This course content needs to be redone by the instructors.

By ephraim o

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Oct 24, 2021

this course is helpful and the video aspect is fine.

how can we have access to the videos covered in each course? i need them for my personal revision. is very important to me please.

By Nugraha S H

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Mar 21, 2020

As I'm not familiar with US healthcare system, the case study given in this course is very confusing to me as there are many unfamiliar words and terms being thrown here and there.

By Gayatri H

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May 31, 2020

The final assignment is not very specific. Its's largely open ended and left up to individual discretion. Please make it quiz based or project based, where results are definitive.

By Vara P

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Jun 22, 2020

The core part of the methodology is not properly covered, it would have been better if the technical information such as tools and the modeling strategies are discussed in depth.

By Farzana S

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May 14, 2020

The course was OK but not up-to the Mark,the case study was quite tough to understand,the case study could have been something simpler so that the beginners can understand well.

By Ryan K

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Nov 8, 2018

Using a case study to illustrate the ideas is great. But it will be better if a less complicated example can be used to help following the concepts easier and better understood.

By Chetan K

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Jan 16, 2020

An easier and more relatable case study would exponentially increase understanding. The present one had complex medical terms and added a layer of complexity to the course.

By adwayt n

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Mar 5, 2019

It was very theoretical and, at times, a little boring as well. I was hoping for more of a hands on experience. But it was definitely very instructive and educational.

By Ramkumar G

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Sep 24, 2019

Since we are following a track, the previous two courses were basic and in this course we came across to lot of data science terminology without proper introduction.

By PHILIPPE L

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Mar 28, 2024

I found it less instructive that module 2 (Data Science Tools). Also, I could not use properly the lab modules. I had some message error when I run the code cells.

By Umaimah Z

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Jul 8, 2019

The example provided was not good at all to follow on the concepts. i had a hard time following up with the video since very little time was spent on each concept.

By Marnilo C

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Apr 25, 2019

The discussions were too introductory. This would be acceptable had there been links to resources which provided more detailed information on this important topic.

By Micatty B

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Dec 9, 2019

The final assignment is not clear

Data preparation and modeling quite confusing for someone with no prior knowledge in data manipulation and statistical background

By Kuldeep R

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Jul 10, 2022

COurse provides some initial theoretical information but the practical exercises are ofno use. Proper schedule of practical be followed and the instructions for

By Jayan T

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Oct 22, 2018

Its an important topic for data scientists, but wish it was taught in a more interesting way with multiple examples of different types instead of one case study.

By Siddhartha P

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Apr 21, 2019

Very short and filled with too much jargons. A much simpler case study would have been great instead of deep diving into the world of Life Science & Healthcare

By Declan H M G

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May 13, 2019

I found the material here vague and difficult to follow at times. Which led to confusion particularly about what was expected with the peer graded assignment.

By Vladislav G

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Jan 25, 2020

Well, when the previous courses in the specialization were a total waste of time, this one is adequate, but still not very usefull for data science itself.

By Wilbert V G

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Jun 3, 2021

The speaking is too fast and the slides don't help much to follow up the explanation. I found it is better just to read the transcript at my own pace :-)

By Alok M

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Jan 12, 2020

Better problems (more generalized and relatable) could have been used to describe and make the modules understand better. Not satisfied with this course.

By olu

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Mar 31, 2020

Teaches what it's supposed to but could be more indepth in establishing your understanding of the process of methodology from Analysis to Evaluation

By saman e

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Sep 11, 2024

The way of teaching was good but i had some issues with marking system. I also reported the issue. But i think learning experience was great to me.

By Alirz110

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May 4, 2021

This information is replicated and immersed in the workplace of a data science expert.

In my opinion, there was no need to attend a separate course.

By Lahiri B

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Oct 13, 2020

Questions asked during the course videos were repetitive and three of them could not be submitted due to some error, despite trying multiple times.