SAS(R) Visual Statistics in SAS(R) Viya(R): Interactive Model Building

Course code: SVSO35

This course introduces SAS Visual Statistics for building predictive models in an interactive, exploratory way. Exploratory model fitting is a critical step in modeling big data.

The classroom and Live Web course is appropriate for users of SAS Visual Analytics in SAS Viya 3.5. In e-learning, there is a course for users of SAS Visual Analytics in SAS Viya 3.5, and there is also a course for users of SAS Visual Analytics in SAS Viya 2020.1.

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Course dates

Starting date: Upon request

Type: E-learning

Course duration: 14 hours

Language: en

Price without VAT: 720 EUR


Starting date: Upon request

Type: Upon request

Course duration: 14 hours

Language: en

Price without VAT: 1 200 EUR


Type Course
Language Price without VAT
Upon request E-learning 14 hours en 720 EUR Register
Upon request Upon request 14 hours en 1 200 EUR Register
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Target group

Predictive modelers, business analysts, and data scientists who want to take advantage of SAS Visual Statistics for highly interactive, rapid model fitting

Course structure

Introduction to SAS Visual Statistics

  • Managing reports and pages.
  • SAS Viya architecture.

Cluster Segmentation

  • Segmentation concepts.
  • Cluster analysis.

Models with Continuous Targets

  • Linear regression models.
  • Generalized linear models.
  • Generalized additive models.
  • Model validation.

Models with Categorical Targets

  • Logistic regression.
  • Modeling with group-by variables.
  • Decision trees.
  • Decision trees in SAS Visual Statistics.

Model Comparison and Scoring

  • Comparing models.
  • Scoring.


Before attending this course, you should have an understanding of regression and logistic regression analysis for predictive modeling. You can gain this knowledge from the Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression course. You should also have experience using SAS Visual Analytics, which you can gain from the SAS Visual Analytics 1 for SAS Viya: Basics course.

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