When does class start/end?
Classes begin promptly at 9:00 am, and typically end at 5:00 pm.
This course provides the fundamentals of using IBM SPSS Modeler and introduces the participant to data science. The principles and practice of data science are illustrated using the CRISP-DM...
Read MoreThis course provides the fundamentals of using IBM SPSS Modeler and introduces the participant to data science. The principles and practice of data science are illustrated using the CRISP-DM methodology. The course provides training in the basics of how to import, explore, and prepare data with IBM SPSS Modeler v18.1.1, and introduces the student to modeling.
- Business analysts - Data scientists - Clients who are new to IBM SPSS Modeler or want to find out more about using it
- It is recommended that you have an understanding of your business data
1. Introduction to data science- List two applications of data science- Explain the stages in the CRISP-DM methodology- Describe the skills needed for data science2. Introduction to IBM SPSS Modeler- Describe IBM SPSS Modeler's user-interface- Work with nodes and streams- Generate nodes from output- Use SuperNodes- Execute streams- Open and save streams- Use Help3. Introduction to data science using IBM SPSS Modeler- Explain the basic framework of a data-science project- Build a model- Deploy a model4. Collecting initial data- Explain the concepts "data structure", "of analysis", "field storage" and "field measurement level"- Import Microsoft Excel files- Import IBM SPSS Statistics files- Import text files- Import from databases- Export data to various formats5. Understanding the data- Audit the data- Check for invalid values- Take action for invalid values- Define blanks6. Setting the of analysis- Remove duplicate records- Aggregate records- Expand a categorical field into a series of flag fields- Transpose data7. Integrating data- Append records from multiple datasets- Merge fields from multiple datasets- Sample records8. Deriving and reclassifying fields- Use the Control Language for Expression Manipulation (CLEM)- Derive new fields- Reclassify field values9. Identifying relationships- Examine the relationship between two categorical fields- Examine the relationship between a categorical field and a continuous field- Examine the relationship between two continuous fields10. Introduction to modeling- List three types of models- Use a supervised model- Use a segmentation model
Save up to $250-$2500 Use Promo Code: SurfBoard
View Details Register by September 6, 2019