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IBM SPSS Modeler Foundations (V18.2)
Course Description
Overview
This course provides the foundations 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 v18.2, and introduces the student to modeling.
Objectives
Introduction to IBM SPSS Modeler
- Introduction to data science
- Describe the CRISP-DM methodology
- Introduction to IBM SPSS Modeler
- Build models and apply them to new data
Collect initial data
- Describe field storage
- Describe field measurement level
- Import from various data formats
- Export to various data formats
Understand the data
- Audit the data
- Check for invalid values
- Take action for invalid values
- Define blanks
Set the unit of analysis
- Remove duplicates
- Aggregate data
- Transform nominal fields into flags
- Restructure data
Integrate data
- Append datasets
- Merge datasets
- Sample records
Transform fields
- Use the Control Language for Expression Manipulation
- Derive fields
- Reclassify fields
- Bin fields
Further field transformations
- Use functions
- Replace field values
- Transform distributions
Examine relationships
- Examine the relationship between two categorical fields
- Examine the relationship between a categorical and continuous field
- Examine the relationship between two continuous fields
Introduction to modeling
- Describe modeling objectives
- Create supervised models
- Create segmentation models
Improve efficiency
- Use database scalability by SQL pushback
- Process outliers and missing values with the Data Audit node
- Use the Set Globals node
- Use parameters
- Use looping and conditional execution
Audience
- Data scientists
- Business analysts
- Clients who are new to IBM SPSS Modeler or want to find out more about using it
Prerequisites
- Knowledge of your business requirements
Topics
Introduction to IBM SPSS Modeler
- Introduction to data science
- Describe the CRISP-DM methodology
- Introduction to IBM SPSS Modeler
- Build models and apply them to new data
Collect initial data
- Describe field storage
- Describe field measurement level
- Import from various data formats
- Export to various data formats
Understand the data
- Audit the data
- Check for invalid values
- Take action for invalid values
- Define blanks
Set the unit of analysis
- Remove duplicates
- Aggregate data
- Transform nominal fields into flags
- Restructure data
Integrate data
- Append datasets
- Merge datasets
- Sample records
Transform fields
- Use the Control Language for Expression Manipulation
- Derive fields
- Reclassify fields
- Bin fields
Further field transformations
- Use functions
- Replace field values
- Transform distributions
Examine relationships
- Examine the relationship between two categorical fields
- Examine the relationship between a categorical and continuous field
- Examine the relationship between two continuous fields
Introduction to modeling
- Describe modeling objectives
- Create supervised models
- Create segmentation models
Improve efficiency
- Use database scalability by SQL pushback
- Process outliers and missing values with the Data Audit node
- Use the Set Globals node
- Use parameters
- Use looping and conditional execution
Recognition
When you complete the Instructor-Led version of this course, you will be eligible to earn a Training Badge that can be displayed on your website, business cards, and social media channels to demonstrate your mastery of the skills you learned here.
Learn more about our IBM SPSS Badge Program →Related Courses
-
IBM SPSS Modeler Foundations (V18.2)
0E069GS- Duration: 16 Hours
- Delivery Format: Self-Paced Training
- Price: 863.00 USD
-
Introduction to Machine Learning Models Using IBM SPSS Modeler (V18.2)
0A079G- Duration: 16 Hours
- Delivery Format: Classroom Training, Online Training
- Price: 1,630.00 USD
This course is eligible for the IBM SPSS Modeler Foundations (V18.2) - Code: 0A069G
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- Same in-demand topics as instructor-led public and private classes.
- Standalone learning or supplemental reinforcement.
- e-Learning content varies by course and technology.
- View the Self-Paced version of this outline and what is included in the SPVC course.
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Self-Paced Training Terms & Conditions
THIS IS A SELF-PACED VIRTUAL CLASS. AFTER YOU REGISTER, YOU HAVE 365 DAYS TO ACCESS THE COURSE.
This is a Self-Paced virtual class; it is intended for students who do not need the support of a classroom instructor. If you feel you would better benefit from having access to a Subject Matter Expert, please enroll in the Instructor-Led version instead. Minimal technical support is provided to address issues with accessing the platform or problems within the lab environment.
Before you enroll, review the system requirements to ensure that your system meets the minimum requirements for this course. AFTER YOU ARE ENROLLED IN THIS COURSE, YOU WILL NOT BE ABLE TO CANCEL YOUR ENROLLMENT. You are billed for the course when you submit the enrollment form. Self-Paced Virtual Classes are non-refundable. Once you purchase a Self-Paced Virtual Class, you will be charged the full price.
After you receive confirmation that you are enrolled, you will be sent further instructions to access your course material and remote labs. A confirmation email will contain your online link, your ID and password, and additional instructions for starting the course.
Upon receipt of the Order Confirmation Letter which includes your Enrollment Key (Access code); the course begins its twelve (12) month access period. IMPORTANT!!! If your course provides access to a hands-on lab (Virtual Lab Environment), you will have a specific number of days (typically 30 days) on the remote lab platform to complete your hands-on labs. Do not start your lab until you are ready to use your lab time effectively. Time allotted in the virtual lab environment will be indicated once you apply the enrollment key. 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.
If the course requires a remote lab system, the 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. Note: This does not add additional days to your Lab Environment time frame.
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