|Kurskode||0E042NO||Leveringsform||Self-paced Virtual Class|
NOK 4 000,00 u. moms
NOK 4 000,00 m. moms
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 'Clustering and Association Models with IBM SPSS Modeler' classroom course. This self paced training course demonstrates how to segment or cluster data with all the clustering techniques available in IBM SPSS Modeler. The course also provides examples of creating association models to find rules describing the relationships among a set of items, and of creating sequence models to find rules describing the relationships over time among a set of items.
This course follows the Introduction to IBM SPSS Modeler and Data Mining course or the Advanced Data Preparation with IBM SPSS Modeler and is designed for anyone who wishes to become familiar with the full range of modeling techniques available in IBM SPSS Modeler to segment (cluster) data and to create models with association or sequence data. For people wishing to successfully build such models using IBM SPSS Modeler, this course is an essential part of the learning process.