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Learner Reviews & Feedback for Tools for Data Science by IBM

4.5
stars
28,118 ratings

About the Course

In order to be successful in Data Science, you need to be skilled with using tools that Data Science professionals employ as part of their jobs. This course teaches you about the popular tools in Data Science and how to use them. You will become familiar with the Data Scientist’s tool kit which includes: Libraries & Packages, Data Sets, Machine Learning Models, Kernels, as well as the various Open source, commercial, Big Data and Cloud-based tools. Work with Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. You will understand what each tool is used for, what programming languages they can execute, their features and limitations. This course gives plenty of hands-on experience in order to develop skills for working with these Data Science Tools. 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. Towards the end the course, you will create a final project with a Jupyter Notebook. You will demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers....

Top reviews

ED

Aug 14, 2022

I love the detailing of every aspect of this course. The Labs, the free subscriptions and free trials provided by IBM Skills Network, everything has been so amazing. Thank you Coursera, thank you IBM.

MO

Apr 17, 2023

the best course for the beginner who is going to start his data science journey. This course tells you all options like tools, libraries, programming languages, etc. Highly recommended for beginners.

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3026 - 3050 of 4,592 Reviews for Tools for Data Science

By Matthew A

Feb 8, 2019

Pretty comprehensive. Good to get familiar with open-source tools.

By Semilogo O

Jul 18, 2023

Overall very informative and supported by lab task for application

By Rajnish S

Jun 23, 2022

Adetaileed course on tools belonging to the field of data science.

By Selene E A H

Mar 1, 2022

Me gustaria mas practicas en las que tuvieramos que explorar datos

By Imron D

Sep 1, 2020

I've learned a lot despite the poor quality of most of the videos.

By E. R " A

Sep 19, 2019

I love tools. I love Open Source tools for Data Science even more!

By Felix B

Mar 4, 2019

Very nice introduction which definitely made me want to know more.

By Peter A

Nov 29, 2018

Good course but some of the IBM Cloud material needs to be updated

By Jennifer E

Oct 16, 2022

good course but some actualizations are needed in watson studio.

By Dhruv G

Jan 13, 2019

The course was great as it describes about the open source tools.

By Won J H

Dec 9, 2020

Great review for tools of data science!! Must take this lecture!

By Federico M

Apr 28, 2020

Some things for the last assignment were not explained very well

By Nanduri V P S A

Apr 4, 2020

Good to know about certain tools which would be useful in future

By Ann S

Feb 11, 2020

week 3 was very confusing as the video was severely out of date.

By Mohamed A

Feb 2, 2020

Great course, would love more work examples to improve my skills

By AbdAllah E

May 6, 2019

I didn't appreciate the marketing tactics for the watson studio.

By Heba M

Dec 24, 2018

Thank you. Very helpful and motivating to explore various tools.

By Irene H

Jan 17, 2023

The instructions for the skills labs didn't always work for me.

By Known S

Nov 6, 2019

The course wholely covered IBM watson and other IBM cloud tools

By Sean M

Aug 13, 2019

I would like to see this course give more hands on assignments.

By Teofilo E d A e S

Apr 1, 2019

I finished the course with the understand of doing basic stuff.

By Ahmed B

Mar 5, 2019

We need more tutorials on all tools demonstrated in this course

By ELAMPARITHI R

Jan 10, 2019

The lab exercises should be more interactive and better planned

By Dianne G

Feb 2, 2024

The R lab environment needs some attention. But good overall.

By otieno a

Jun 11, 2023

The knowledge that this course gives the learner is invaluable