Learner Reviews & Feedback for Tools for Data Science by IBM

4.5

stars

29,164 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

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.

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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1051 - 1075 of 4,762 Reviews for Tools for Data Science

By Vijay N

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Jul 18, 2019

Very interactive course to learn the tools and get familiar with .

By Pappu R M

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Jul 5, 2019

Great course give overview of Open sources tools like Data Science

By Joao C M

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May 8, 2019

Broader view of the tools to support the data scientist activities

By Bakyt N

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Jan 22, 2019

Very good introduction to various tools with emphasis on IBM tools

By Rajakumari R

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Aug 18, 2023

The course Tools for Data Science is very useful and informative

By Dr. N G

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Apr 7, 2023

A great source of learning about data science tools and languages

By Jose R

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Jun 14, 2022

I liked it, but I should've believe it was really for beginners!

By Sovan S

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Jan 15, 2022

The course is excellent to understand the basics of Data Science.

By Tan C K

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Sep 8, 2021

Superb! I started to have an overview of Data Science. Thank you!

By OMPRAKASH V

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Aug 22, 2020

This is good course for data science. I learned from this course.

By Fadhel H D

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May 25, 2020

Give me a good knowledge about tools we can use for data science.

By BHARGAV A

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May 12, 2020

Good course on introduction to open source tools for data science

By Hannan K

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Apr 30, 2020

Good start to have an understanding of tools used in Data Science

By Jesús A J P

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Nov 24, 2019

Te enseña lo básico de las herramientas open source de Notebooks.

By Uche C O

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May 29, 2019

Great course for learning about the common tools for data science

By Laura C G B

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Apr 21, 2019

Muy completa la guía para empezar a implementar las herramientas.

By Miguel A T J

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Aug 13, 2023

This is a great course, shows the fundamentals for Data Science.

By Ishtiaq A

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Jul 4, 2023

A great course, I have learned a lot in this course, Thanks IBM.

By Tales L

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Feb 9, 2023

Excellent! I feel pretty much familiarized with the basic tools.

By Sunidhi K

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Dec 7, 2022

that was very learnable application and practical implementation

By ABHISHEK G M

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Mar 29, 2020

It was very nice course on introduction to the open source tools

By Adrian L

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Jan 23, 2020

The course was excellent covering all the basics for a beginner.

By Arya K N

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Jan 6, 2020

Good and very informative module. Well explained all the tools .

By Juan C

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Nov 17, 2019

Videos should be updated to the new version of IBM Watson Studio

By Raymond M A

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Oct 21, 2019

una buen experiencia para empezar a analizar al ciencia de datos