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IBM SPSS Modeler Foundations on IBM Cloud Pak for Data (V2.5.x) eLearning

This IBM Web-Based Training (WBT) is Self-Paced and includes: - Instructional content available online for duration of course - Visuals without hands-on lab exercises SPSS Modeler is available on IBM...

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$249 USD GSA  $127.82
Course Code 6X234G-WBT
Duration 6 hours
Available Formats Self Paced
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This IBM Web-Based Training (WBT) is Self-Paced and includes:
- Instructional content available online for duration of course
- Visuals without hands-on lab exercises

SPSS Modeler is available on IBM Cloud Pak for Data V2.5. This course reviews the basics of how to import, explore, and prepare data, and introduces the student to machine learning models with SPSS Modeler on Cloud Pak for Data.

Skills Gained

- Introduction to SPSS Modeler on IBM Cloud Pak for Data- Import and explore the data- Integrate data- Transform fields- Identify relationships- Introduction to Modeling

Who Can Benefit

Clients who are new to IBM SPSS Modeler on IBM Cloud Pak for Data or who want to find out more about using it.

Prerequisites

Knowledge of your business requirements.

Course Details

Course Outline

Introduction to SPSS Modeler on IBM Cloud Pak for Data- Introduction to data science- Describe the CRISP-DM methodology- Introduction to SPSS Modeler- Build models and apply them to new data Import and explore the data- Describe key terms in working with data- Import and export data- Audit the data- Define missing values Integrate data- Identify the unit of analysis- Remove duplicate records and aggregate data- Append and merge datasets- Append and merge datasets with incomplete data Transform fields- Use the Control Language for Expression Manipulation- Derive fields- Use functions- Reclassify fields Identify relationships- Overview of the nodes to use- Explore the relationship between two categorical fields- Explore the relationship between a categorical field and a continuous field- Explore the relationship between two continuous fields Introduction to Modeling- Identify three types of machine learning models- Identify three types of supervised models- Identify unsupervised models- Deploy machine learning models

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