Open Source tools for Data Science

Coursera Open Source tools for Data Science

Platform
Coursera
Provider
IBM
Effort
2-3 hours/week
Length
3 weeks
Language
English
Credentials
Paid Certificate Available
Part of
Course Link
Overview
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.

Syllabus
Introducing Cognitive Class Labs
This week, you will get an overview of the various data science tools available to you, hosted on Cognitive Class Labs. You will create an account and start exploring some of the features.

Jupyter Notebooks
This week, you will learn about a popular data science tool, Jupyter Notebooks, its features, and why they are so popular among data scientists today.

Apache Zeppelin Notebooks
This week, you will learn about Apache Zeppelin Notebooks, its feature, and how they are different from Jupyter Notebooks.

RStudio IDE
This week, you will learn about a popular data science tool used by R programmers. You'll learn about the user interface and how to use its various features.

IBM Data Science Experience
This week, you will learn about an enterprise-ready data science platform by IBM, called Data Science Experience. You'll learn about some of the features and capabilities of what data scientists use in the industry.

Project: Create and share a Jupyter Notebook

Taught by
Polong Lin
Author
Coursera
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