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Learner Reviews & Feedback for Data Science Methodology by IBM

4.6
stars
19,896 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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1751 - 1775 of 2,502 Reviews for Data Science Methodology

By Diogo M

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Sep 8, 2023

Although we can gather a lot of knowledge from this course, many of the lessons didn't have the transcript and many others only offered Turkish transcripts instead of English.

By Rohit S

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May 4, 2020

It is a very good course for the beginners as I got all the basic - basic information about the process in data science and machine learning which would be used in the future.

By CH

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Jun 1, 2019

This course finally gets into the nuts and bolts of data science. The very specific examples with Python code shown make this the right introduction to the rest of the course.

By Janhavi D

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Aug 20, 2019

It is great introduction for someone who has no idea about data science. The methodology is clearly explained. However, the example discussed is a little difficult to follow.

By Suchitra K

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Mar 7, 2020

I'm very thankful to this course because it neatly explain the step followed in the data science project.Also the quizzes help me to avoid misunderstanding of the concepts.

By Valentina G

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Feb 21, 2020

A good introduction, but as you learn you also need to further explore and read more. I would have loved to see a list of readings providing more examples and case studies.

By Deleted A

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May 15, 2019

The methodology seems a bit arbitrarily devised to give 10 parts though the 10 are sometimes not meaningfully distinct.

Still a well structured approach to breaking it down.

By Chris R

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Apr 16, 2020

This course compresses much material about approaches and modelling, and describes only a few of the concepts in any real detail. Though, what is presented is done well.

By Steven N

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Feb 17, 2019

Case study isn't suitable for all categories of student ... i didn't understand the case study because i have no medical background plus there was hard expressions for me

By Alan J

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Apr 27, 2020

It was exceptionally good, with case-study driven content and accurate explanation of the different terms and condition before moving to a data science specific problem.

By vivens m

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Mar 20, 2020

This course is great except that it has problem of labs which are not working correctly too many times. It is really challenging because too often it seems it is offline

By Alexandru S

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Apr 17, 2019

Interesting course, although some very "thick" notions. It looses 1 star because of the final assignment, which is very vague and open to all kind of interpretations.

By Sisir K

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Jan 13, 2019

Very informative. The case study discussed was not very interesting to me, but everything was very easy to follow. The interactive labs helped with hands-on learning.

By Christoph W

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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

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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

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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

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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

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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.

By LEI G

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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

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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 Liuliu Q

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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

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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

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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

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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

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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.