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Course Outline
Introduction
- Overview of advanced analytics and data mining
- Overview of CRISP-DM
- Understanding the Modeler UI
- Understanding the mechanics of building streams
Understanding Data
- Reading data into Modeler
- Measurement level and field roles
- Using the data audit node
Data Preparation
- Selecting cases
- Reclassifying categorical values
- Using append node and merge node
- Deriving fields
Modeling
- Overview of modeling
- Using a partition node
- Building a CHAID model
- Model assessment
Evaluation and Deployment
- Using analysis and evaluation node
- Scoring new data and exporting
- Using flat file node
Troubleshooting
Summary and Next Steps
Requirements
- No data mining background needed
Audience
- Data analysts
- Anyone who wants to learn about SPSS Modeler
14 Hours
Testimonials (2)
I feel more confident with coding now. I've never done it before but now I understand that it's not rocket science and I can do it when necessary.
Anna - Birmingham City University
Course - Foundation R
The content, as I found it very interesting and think it would help me in my final year at University.