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Introduction to IBM SPSS Modeler and Data Science (v18.1.1)
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 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.
- Introduction to data science
- Introduction to IBM SPSS Modeler
- Introduction to data science using IBM SPSS Modeler
- Collecting initial data
- Understanding the data
- Setting the of analysis
- Integrating data
- Deriving and reclassifying fields
- Identifying relationships
- Introduction 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 science
2. 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 Help
3. Introduction to data science using IBM SPSS Modeler
• Explain the basic framework of a data-science project
• Build a model
• Deploy a model
4. 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 formats
5. Understanding the data
• Audit the data
• Check for invalid values
• Take action for invalid values
• Define blanks
6. Setting the of analysis
• Remove duplicate records
• Aggregate records
• Expand a categorical field into a series of flag fields
• Transpose data
7. Integrating data
• Append records from multiple datasets
• Merge fields from multiple datasets
• Sample records
8. Deriving and reclassifying fields
• Use the Control Language for Expression Manipulation (CLEM)
• Derive new fields
• Reclassify field values
9. 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 fields
10. Introduction to modeling
• List three types of models
• Use a supervised model
• Use a segmentation model
When you complete the Instructor-Led version of this course, you will be eligible to earn an IBM 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 Modeler Badge Program →
- Duration: 8 Hours
- Delivery Format: Self-Paced Training
- Price: 525.00 USD
- Duration: 8 Hours
- Delivery Format: Classroom Training, Online Training
- Price: 815.00 USD
Self-Paced Training Info
Learn at your own pace with anytime, anywhere training
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Self-Paced Training Terms & Conditions
THIS IS A SELF-PACED VIRTUAL CLASS. AFTER YOU REGISTER, YOU HAVE 30 DAYS TO COMPLETE 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.
You can start the course at any time within 12 months of enrolling for the course. After you register/start the course, you have 30 days to complete your course. Within this 30 days, 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.
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