Open Source tools for Data Science
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Open Source tools for Data Science

$38.00

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, RStudio IDE, Apache Zeppelin and Data Science Experience. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. read more…

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Description

What you'll learn

Introducing Skills Network Labs

Jupyter Notebooks

Apache Zeppelin Notebooks

RStudio IDE

IBM Watson Studio

Project: Create and share a Jupyter Notebook

Description

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, RStudio IDE, Apache Zeppelin and Data Science Experience. 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 Cognitive Class 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 Data Science Experience and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

Requirements

Access to a computer or mobile device with an internet connection.

Motivation to learn!

There are no special materials or prerequisite knowledge required for this course.

Who this course is for

Students who are new to this field

Students willing to put in a couple hours to learn about Open Source tools for Data Science

Advanced students wanting to add another skill to their portfolio

Content Creator

Polong Lin – Data Scientist – IBM Developer Skills Network

This course includes

Participation Confirmation/Certificate

Option for learning at your own pace

Videos and reading material about the course

Practice tests

Assessed tasks with feedback from other course participants

Evaluated tests with feedback

Evaluated programming tasks

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