Learners will be able to design end-to-end analytical workflows, prepare and transform data, apply statistical and machine learning models, interpret results, and communicate actionable insights using SPSS Modeler. By the end of this course, learners will confidently build, execute, validate, and optimize analytical streams aligned with real-world business problems.
Apply Data Analytics Using SPSS Modeler Workflows
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Design end-to-end analytical workflows in SPSS Modeler using stream-based, visual analytics.
Prepare, transform, and model data using statistical and machine learning techniques.
Interpret, validate, and communicate analytical results to support real-world business decisions.
Details to know
Shareable certificate
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Recently updated!
February 2026
Assessments
28 assignments
Taught in English
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There are 7 modules in this course
This module introduces learners to SPSS Modeler, its analytical significance, visual workflow design, security fundamentals, and core modeling node concepts required to build structured data science streams.
What's included
8 videos4 assignments
This module focuses on understanding domain-specific datasets, performing data preparation, and interpreting statistical summaries to establish a strong analytical foundation before modeling.
What's included
8 videos4 assignments
This module develops skills in interpreting analytical outputs, applying segmentation techniques, and exporting model results for downstream consumption and decision-making.
What's included
8 videos4 assignments
This module covers the architectural design of SPSS Modeler streams, execution flow management, recovery mechanisms, and advanced data operations for reliable analytics.
What's included
9 videos4 assignments
This module emphasizes result interpretation, dashboard visualization, execution scenario analysis, and default configuration best practices to support insight communication.
What's included
8 videos4 assignments
This module explores advanced statistical modeling, neural network concepts, execution dependencies, and reporting techniques for complex analytical solutions.
What's included
8 videos4 assignments
This capstone module integrates stream design, execution, validation, and result communication to deliver complete, decision-ready analytical solutions.
What's included
10 videos4 assignments
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