Introduction to IBM SPSS Modeler and Data Mining - SPVC

What is it about?

This is the self paced training version of 'Introduction to IBM SPSS Modeler and Data Mining' classroom course. This course will show you how to use IBM SPSS Modeler to automate the building of predictive models. The course will show you how to build predictive models for customer behavior and build customer segmentation using various cluster models. You will learn how to read data from various sources and automatically prepare data for modeling using a variety of methods. Scoring new data using the model will also be discussed.

Who is it for?

This basic course is for anyone with little or no experience using IBM SPSS Modeler (formerly Clementine) or with data mining in general.

Prerequisites:

You should have:

• General computer literacy.

It would be helpful if you had:

• an understanding of your organization's data, as well as any of your organization's business issues that are relevant to the use of data mining.

No statistical background is necessary.

Topics:

1. Introduction to data mining
2. The CRISP-DM methodology
3. Best practices for data mining
4. The basics of using IBM SPSS Modeler
5. Reading data files
6. Working with dates
7. Auditing and exploring data quality
8. Searching for anomalous data and outliers
9. Data manipulation
10. Searching for relationships among fields
11. Combining data files by appending and/or merging
12. Restructuring data files with aggregate
13. Sampling data
14. Partitioning data for modeling
15. Modeling techniques in IBM SPSS Modeler
16. Automatic Modeling for Binary Outcomes
17. Evaluating and comparing model performance
18. Deploying and using models
19. Running IBM SPSS Statistics commands from IBM SPSS Modeler