|Course code||0V101||Skill level||Intermediate|
|Duration||1.0 days||Delivery type||Web Based Training|
|Course type||Public only|
|Public price||See Partner website|
NOTE: THIS IS AN ONLINE SELF-PACED COURSE. PLEASE DO NOT MAKE TRAVEL ARRANGEMENTS FOR THIS COURSE.
This course is delivered as an online self-paced course, and will be available to you 24 hours a day, seven days a week, for a 1-year period from the time of enrollment. There is no instructor for this course. Choose any of the course instances listed under the course schedule to enroll, and you will receive information on how to access the course in 2-3 business days. After the enrollment, you will have access to the course for 1-year. (Please note: once you enroll in this course, you will not be able to unenroll.)
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This eLearning offering is a Web-based Training (WBT). IBM SPSS WBTs are interactive multimedia modules that are intuitive and instructionally sound. Through visual content and audio, product demonstrations, hands-on learning activities, and simulation-based assessments and quizzes, the modules guide the students to mastering an IBM SPSS application.
IBM SPSS Modeler Advantage and Rules Management (V7) is a web-based training course that teaches new business users of IBM SPSS Modeler Advantage how to build, evaluate and deploy predictive models, clustering models and association models. Various business questions will be addressed, among these are: analyzing responses in database marketing, churn (or retention) in Telco, fraud in insurance, and market basket analysis in retail. Also, this course will discuss how to build models using ''''statistical'''' algorithms, how to build models by user-defined rules and how statistical modeling and user-defined modeling can be combined to optimize results. Finally, ways to manage rules are reviewed, using IBM SPSS Rules Management.
Training Paths that reference this course are:
IBM SPSS Modeler Advantage in Perspective
Classification: Interactive Modeling
Classification: Auto Modeling
Evaluating Classification Models
Scoring Classification Models