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Learner Reviews & Feedback for Tools for Data Science by IBM

4.5
stars
28,245 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 4,607 Reviews for Tools for Data Science

By David P

Jun 13, 2019

An exciting start to the actual work of data science using IBM tools.

By Humayun A

Apr 20, 2019

need to explain what we will learn from this week materials and quiz.

By Navaneetha K R

Apr 4, 2019

Course gives a overall view of how to use various data science tools.

By asher b

Sep 14, 2018

Succinct high-level overview. Still need more courses to get skilled.

By Leo S

Oct 15, 2022

its so good to learn ,but its also little bit harder to understand.

By Juan D P M

Feb 11, 2022

i would liked more practic labs on the course, but overall is good.

By Kwaku B

Jul 18, 2020

It needs more real-world or direct workplace data sources to work on

By Robert W

Mar 4, 2020

Excellent course. It was perfectly paced, the videos were excellent,

By Georgios G

Oct 25, 2019

The IBM videos for using the IBM experience module should be updated

By Jeffrey K

Sep 4, 2018

Why not just write with a Jupyter notebook from your own web browser

By Hazem A M S

Sep 15, 2021

Sufficient moderate detailed information of IBM Watson Studio tools

By Joshua

Jul 26, 2020

Insightful thou though but all the effort and extra reading pay off

By Rubén Q “ H D M

Apr 15, 2020

Skills acquired from tools like, Jupyter notebooks, R, Scale, Spark

By Prateek G

Mar 18, 2020

Good course on introduction of various tools used 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!