Learner Reviews & Feedback for Tools for Data Science by IBM

4.5

stars

30,282 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

Sep 21, 2020

Gives you a good idea and overview about different tools but can be overwhelming because of the amount of new information and some videos are not up to date. Week 3 especially had some weak videos.

Apr 12, 2020

It serves perfecty its aim that is giving a first glance of the open course tools for data science. Of course each tool is briefly touched and it hands over the student the duty to deepen each tool.

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1076 - 1100 of 4,969 Reviews for Tools for Data Science

By Sandro J H G

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Sep 24, 2021

Excellent lectures that introduce you to the field of Data Mining.

By Dastin P

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Aug 21, 2021

Great course for who's want to know and explore data science tools

By Harpreet S

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Jul 23, 2021

Very Good course for understanding of all tools of Data Science.

By Khusan T

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Feb 22, 2021

Thank you! Course give the demanding skills in a modern hr-market.

By Azajul I N

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Dec 24, 2020

WOW. I really enjoyed this course. Highly recommended. Keep it up.

By Douglas C

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Aug 14, 2020

Really thorough introduction to open source tools for Data science

By Thushani

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Jul 24, 2020

Excellent content with easy-to-follow instructions and lab guides.

By Towhidul I

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Jul 12, 2020

Learned lots of new things about Data Science tools. Thanks a lot!

By Salman H

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Jun 16, 2020

An excellent course for new learners in the field of Data Science.

By Leandro M T

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May 11, 2020

Buy the promised, very good course.

We learned about various tools

By Yutaka R

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Apr 30, 2020

The material very detail and newbie can learn it without pressure.

By ALABE L W

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Mar 30, 2020

Thank you IBM the course is well structure and self understanding.

By Temitope K

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Mar 5, 2020

It was tough at the beginning....but at the end it became clearer!

By shubhal p

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Feb 18, 2020

Good teaching of

Open Source tools for Data Science

Keep it up...

By Fahad A

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Oct 22, 2019

As a beginning in using some tools of Data Science, it is perfect.

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 TY_A_28_YASH_KAGADE

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Feb 6, 2025

excellent but a human instructor would have been a great addition

By Melvin S

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Feb 3, 2025

Excelente para dar una vista global de las herramientas empleadas

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.