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Introduction to Analytical Decision Management (V17)

IBM Course Code: 0W113G

Vendor# 0S113G

GK# 3340

Course Overview

This course brings the benefit of predictive analytics to real business problems, allowing you to build custom applications tailored to your customers or industry. While applications are typically configured to solve very specific problems, all are based on a common set of capabilities: Automate decisions using business rules; add insight using predictive models; and use prioritization, optimization, or simulation to reach the best decision based on the above. A number of packaged applications are available, tailored to solving specific business problems.

The course will not only cover how to use the packaged applications, but also how to create your own applications; how Analytical Decision Management interplays with IBM SPSS Modeler (v17) and IBM SPSS Collaboration and Deployment Services (v7); and how to deploy results for real-time.

Delivery Format Options

  • Classroom Live

    Classroom Live

    Receive face-to-face instruction at one of our training center locations.

    From

    $1495 CAD

    2 day

  • Virtual Classroom Live

    Virtual Classroom Live

    Experience expert-led online training from the convenience of your home, office or anywhere with an Internet connection.

    From

    $1495 CAD

    2 day

  • Self-Paced

    Self-Paced

    Recordings, hands-on labs and expert instructors empower you to train on your own schedule.

    From

    $720 CAD

    1 session

  • Private Group Training

    Private Group Training

    Train your entire team in a private, coordinated professional development session at the location of your choice.

    Receive private training for teams online and in-person.

Request a date or location for this course.

Who Needs To Attend

This basic course is for business users who want to optimize and automate the millions of decisions made every day. The course is for people who want to be able to:

  • Automate decisions using business rules.
  • Add insight using predictive models.
  • Use prioritization, optimization, or simulation to reach the best decision based on the above