Skip to main content

About This Course

Watson Analytics Fundamentals teaches you the basics of Watson Analytics. Watson Analytics offers you the benefits of advanced analytics without the complexity. A smart data discovery service available on the cloud, it guides data exploration, automates predictive analytics and enables effortless dashboard and infographic creation.You can get answers and new insights to make confident decisions in minutes—all on your own. This is the first version of this course.

Requirements

Basic knowledge of operating systems (UNIX/Linux).

Course Staff

Tony Young

Tony Young

Tony Young is a Technical Curriculum Development Lead and Technical Course Developer for the Predictive and Business Intelligence team within IBM Analytics Education Services. Since joining IBM in 2008 as part of the Cognos acquisition, he has lead a team of technical course developers, and has developed numerous education offerings, including those for the Business Intelligence (Cognos), Predictive Analytics (SPSS), and Financial and Operation Performance Management (Planning) segments. He is currently the lead developer for Watson Analytics how-to video offerings from IBM Analytics Education Services.

Jason Salares

Jason Salares

Jason Salares is an IBM worldwide Watson Analytics evangelist. He joined IBM in 2006 and has worked in different roles including technical support specialist, software instructor, business analytics product demo developer and presenter, and technical sales specialist. Jason is an expert in Watson Analytics and is the technical lead of a worldwide technical evangelist team.

Jackie Ross

Jackie Ross

Jackie Ross is an IBM Watson Analytics Enablement manager based out of Toronto.

Frequently Asked Questions

What web browser should I use?

The Open edX platform works best with current versions of Chrome, Firefox or Safari, or with Internet Explorer version 9 and above.

See our list of supported browsers for the most up-to-date information.

  1. Course Number

    WA0101EN
  2. Classes Start

    Any Time, Self-Paced
  3. Estimated Effort

    359:25
Enroll