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Learner Reviews & Feedback for Tools for Data Science by IBM

22,753 ratings
3,571 reviews

About the Course

What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you'll learn about Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. With the tools hosted in the cloud on Skills Network Labs, you will be able to test each tool and follow instructions to run simple code in Python, R or Scala. To end the course, you will create a final project with a Jupyter Notebook on IBM Watson Studio and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers....

Top reviews

Sep 15, 2020

Absolutely Loved this course!! Challenging at times to keep up with all the terms and processes. The course provided great insight into Data Science. Would highly recommend it as your first course.

Apr 24, 2019

To the contrast of other reviews, I find the content very well bifurcated and fed to the learners. The course very easily digestable and I have had a great amount of fun learning it.. Go for it!!!!

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2251 - 2275 of 3,575 Reviews for Tools for Data Science

By Mohammed H M A

Jun 22, 2020

very nice course but need more improvement in term in that it is dealing with beginner

By Giorgio M

Apr 24, 2020


Straight to the point

Maybe some more example on Watson would be appreciated

By Ashique B Y

Apr 4, 2020

Some course video and links should be updated, i assume. Overall great course. Thanks.

By Anand s

Feb 27, 2020

It is very helpful course to learn basics of open sourse tools or IDE for data science

By Borsali F

Nov 14, 2019

Good for knowing Open Source (and online / no need to download) tools for Data Science

By Vasu N

Jul 11, 2019

Basics of Jupyter Notebook were clear but zepplelin notebook was not that much cleared

By Héctor C

Mar 18, 2019

Good course and good explanations although an update on the content would be welcomed.

By Fayaz O

Feb 7, 2019

Good overview of the different web-based platforms available to practice data science.

By Ewa H

Sep 12, 2018

Great course. One star less for all the difficulties with logging in to Watson Studio.

By Micah K

Oct 28, 2021

Watson studio has a different interface now compared to when this course was created.

By Saju F

May 22, 2020

good course for the beginners who want some hands-on experience in data science tools

By Srinivasa R S R

Feb 4, 2020

Course was well laid out. Systematic and detailed. helps any new bie to Data Science.

By Eugénio M

Sep 24, 2020

Some videos are not very clear, the sound is awful and the sequence is not adequate.

By Ninad M K

Jul 5, 2020

This course basically explain the tools for data science.And it is pretty much cool.

By Gisella B

Feb 25, 2020

Hay videos desactualizados en la semana 3 y me costó poder seguir las instrucciones.

By Anthony L

Jan 20, 2020

High-level introductions of the common data science tools and analytics environment.

By Xiwen L

Oct 29, 2019

Nice intro to different tools. If only it gives more examples or exercises to drill.

By Nathan P

Oct 10, 2019

You will not really be using these tools in this course, they are simply introduced.

By Jozef M

Sep 1, 2019

I've learned about many data sources & created accounts where I can learn. Thanks.

By Thomas T

Aug 20, 2019

Good course, but a little bit unfortunate that the IBM Watson Studio changed design.

By Chris O

Sep 8, 2021

The audio on the videos was not consistent. On some videos, the audio was too low.

By Melissa k

Feb 4, 2020

some videos/ articles are outdated. please update, especially watson studio's part.

By Simpson I

Dec 29, 2019

It Gave me a good basic understanding of the open source tools used in Data science

By Aaron S

Feb 17, 2019

A lot of the videos, especially week 3, are not current with Watson Studio screens.

By Bastian E

Feb 17, 2021

Good course, very clear what to do. In week two might be too many tools presented.