Watson Studio Primer (W7118G-WBT)

Overview

This course is a quick getting started guide to Watson Studio for Data Scientists ranging from a student to professional level. This course will enable learners to be up and running on Watson Studio, using notebooks hosted on IBM cloud to work with their data, no matter where it lives.  

Learners will take away how to work in a collaborative, cloud-based notebook environment using Watson Studio. Learners will see how Watson Studio supports a Data Scientist through the different stages of the Data Science project life-cycle.

 

IBM Customers and Sellers: If you are interested in investing in your training, please consider the following Individual or Enterprise Subscriptions:

  • IBM Learning for Data and AI Individual Subscription (SUBR022G)
  • IBM Learning for Data and AI Enterprise Subscription (SUBR004G)
  • IBM Learning Individual Subscription with Red Hat Learning Services (SUBR023G)

Audience

Anyone who wants to learn the tooling required to perform Data Science in an enterprise environment.

Prerequisites

Some basic understanding of a Data Scientist's role and the Data Science workflow will be helpful, but no prior knowledge of notebooks or a specific programming language will be assumed.

Objective

• Setting Up and Setting the Scene with IBM Watson Studio 
• Gathering and Accessing Data for the team with IBM Watson Studio 
• Prototyping with IBM Watson Studio Collaborative Notebooks

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Course Outline

Setting Up and Setting the Scene with IBM Watson Studio 
• Describe the use case  
• List the steps in the Data Science workflow 
• Add Watson Studio as a service from an existing IBM Cloud account 

Gathering and Accessing Data for the team with IBM Watson Studio 
• Create a project in Watson Studio 
• Invite collaborators and assign permissions 
• Add data to the project from a local file 

Prototyping with IBM Watson Studio Collaborative Notebooks 
• Open a notebook with their desired environment 
• Generate code to import data in the notebook 
• Save notebook versions 
• Share a notebook  
• Describe the steps in the Data Science workflow