Chevron Left
Back to Data Science Methodology

Learner Reviews & Feedback for Data Science Methodology by IBM Skills Network

4.6
stars
18,828 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. Most of the established data scientists follow a similar methodology for solving Data Science problems. In this course you will learn and then apply this methodology that can be used to tackle any Data Science scenario. The purpose of this course is to share a methodology that can be used within data science, to ensure that the data used in problem solving is relevant and properly manipulated to address the question at hand. Accordingly, in this course, you will learn: - The major steps involved in practicing data science - Forming a business/research problem, collecting, preparing & analyzing data, building a model, deploying a model and understanding the importance of feedback - Apply the 6 stages of the CRISP-DM methodology, the most popular methodology for Data Science and Data Mining problems - How data scientists think! To apply the methodology, you will work on a real-world inspired scenario and work with Jupyter Notebooks using Python to develop hands-on experience....

Top reviews

TM

Jun 18, 2021

Very interesting course. It shed a light on what the structured approach really is. It's worth to pause for a moment with every step of the methodology and think how to apply it in real life. Thanks!

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 :)

Filter by:

1726 - 1750 of 2,347 Reviews for Data Science Methodology

By Bhuvana K

Aug 5, 2022

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

By Mauricio F O M

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

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

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

Jul 21, 2019

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

By Partha S D

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

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

May 16, 2020

need more examples if possible,

the readmission example is not clear

the cuisine ingredients example is clear

By Vishakh V

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

Jul 25, 2019

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

By Nwoke C

Jun 3, 2020

The sited examples in this course makes the learning easily understandable. Of course, everyone likes food

By Kumar G

Jun 28, 2022

Understanding Python part without having prior knowledge is confusing & led to somewhat loss of interest.

By VICTOR A C C

Jan 22, 2021

Excellent For Fundamentals on methodology, would like to learn more about Prescriptive Analytic approach.

By Leonardo R

Oct 8, 2018

I think some parts of the course wasn't clear enough, but by researching on google about it helped a lot.

By Samuel L

May 27, 2022

Very good and easy to follow, although more in-depth examples of different model would have been a plus.

By Rohit A

Oct 20, 2019

This course was interesting but I felt that it was slightly confusing to apply for the final assignment.

By Kevin W

Mar 25, 2019

It is a bit challenging for beginners but totally worth it. Ensure you read listen to the material well.

By Monica S

Sep 4, 2018

Pretty solid information. Great for the novice with no background. Loved that it was basic and useful.

By Joshua A (

Jan 27, 2022

Some interactive activities like vocabulary matching may help with recall and word/process definitions.

By Utsav D

Oct 7, 2020

i think this course needs more practice cases so we can get much more comfortable with the methodology

By Siwarak L

Sep 21, 2019

Some of the detail was briefly covered, learners need to research more from other educational sources.

By BAO W

Sep 2, 2019

Since I believe this course is an important stage of the certificate, three sections may be too short.

By Germán G R

Oct 19, 2021

More examples are needed and that the modeling programs have more comments to know what is happening

By Vasanthaenian S

Apr 2, 2020

It gives a brief introduction to Data Science Methodology and explains it well with proper examples.

By Friscian V C

Nov 21, 2019

I enjoyed the course thoroughly but I wish more details were given for a deeper learning experience.