Open Source tools for Data Science
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.
Introducing Skills Network Labs
-This week, you will get an overview of the various data science tools available to you, hosted on the IBM Developer Skills Network Labs (SN Labs). You will create an account and start exploring some of the features.
-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.
-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 Watson Studio
-This week, you will learn about an enterprise-ready data science platform by IBM, called Watson Studio (formerley known as 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