Kurs informasjon: Classifying Customers Using IBM SPSS Modeler (V14.2) SPVC

PLEASE DO NOT MAKE TRAVEL ARRANGEMENT FOR THIS SELF PACED VIRTUAL COURSE (SPVC). ONCE YOU ARE ENROLLED IN THIS COURSE, YOU WILL NOT BE ABLE TO CANCEL YOUR ENROLLMENT.

After you receive confirmation that you are enrolled, you will be sent further instructions to access your course material and remote labs. You will then have a 30 day window in which to complete your course. Within this 30 days, you will have 336 hours of elab time. The self-paced format gives you the opportunity to complete the course at your convenience, at any location, and at your own pace. The course is available 24 hours a day, but lab system access is allocated on a first-come, first-served basis. When you are not using the elab system, ensure that you suspend your elab to maximize your hours available to use the elab system. Once you have accessed the course, help is available Monday through Friday; questions will be responded to within 24 hours.

NO EXTENSIONS FOR THIS COURSE WILL BE GRANTED.

This is the self paced training version of ""Classifying Customers Using IBM SPSS Modeler"" classroom course. Classifying Customers Using IBM SPSS Modeler is a one day, self-paced training, intermediate level course that provides an overview of how to use Modeler to predict the category to which a customer belongs based on selected data. Some examples include: whether a customer switches to another provider or brand, whether a customer responds to a particular advertising campaign, or how well a student will perform in a specific academic setting.

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This intermediate course follows the 'Introduction to IBM SPSS Modeler and Data Mining' course and is essential for anyone who wishes to become familiar with a number of modeling techniques available in IBM SPSS Modeler used to classify customers. This would include Data Analysts and analytics business users.

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You should have:

• Experience using IBM SPSS Modeler

Recommended:

• Prior completion of Introduction to IBM SPSS Modeler and Data Mining.

An introductory course in statistics, or equivalent experience, is helpful.

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Please refer to course overview.

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• Classifying Customers in Context
• Classifying Customers with Rule Induction Models (interactive and direct mode)
• Classifying Customers with Statistical Models
• Classifying Customers with Machine Learning Models

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eLabs will be available for a total of 336 hours in the 30 day window.

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Minimum Requirements (for PC) to use SPVC

• Windows 2000, XP, Vista, and 7
• Firefox, including V3.6.6
• Internet Explorer, including V8
• browser settings include:
  • Java Runtime Environment must be installed and enabled in the web browser
  • Web browser must be set to enable/allow JavaScript
  • Web browser Pop-up blocking mechanisms must be set to allow pop-ups from elearn.ihost.com
  • Cookies must be enabled
  • Flash-enabled
  • ActiveX-enabled

• CITRIX, for the remote lab (instructions to install included with the SPVC)

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