This course discusses the theoretical foundation for different techniques associated with supervised machine learning models. A series of demonstrations and practices is used to reinforce all the concepts and the analytical approach to solving business problems

This course provides an introduction to data preparation, data discovery, and report creation in SAS Visual Analytics. The e-learning version of this course provides access to SAS Viya for Learners, which enables students to use the software to complete the practices

Getting Started with SAS Visual Analytics

• Introduction to SAS Visual Analytics.
• Exploring the SAS Visual Analytics course environment.
• Viewing SAS Visual Analytics reports.

Preparing Data in SAS Visual Analytics

This course highlights SAS Viya, our open platform built for analytics innovation. Learn how to Describe what SAS Viya is and explain how the related products are used. Anyone who wants to learn at a high level the capabilities of SAS Viya and the related products

SAS Viya Administration

• overview of SAS Viya Deployment options
• bridging SAS 9 and SAS Viya
• accelerating SAS DATA Step performance with SAS Viya

Transitioning from SAS 9 to SAS Viya

This course provides an overview of the platform for SAS Business Analytics from a platform administrator's perspective. There are no formal prerequisites for this course. This course addresses SAS Analytics Platform, SAS Management Console software

This course is for users who want to learn how to write SAS programs to access, explore, prepare, and analyze data. It is the entry point to learning SAS programming for data science, machine learning, and artificial intelligence. It is a prerequisite to many other SAS courses

Learn how to

SAS Programming 1

This course is for experienced R users who want to apply their existing skills and extend them to the SAS environment. Emphasis is placed on programming and not statistical theory or interpretation

Students in this course should have knowledge of plotting, manipulating data, iterative processing, creating functions, applying functions, linear models, generalized linear models, mixed models, stepwise model selection, matrix algebra, and statistical simulations.

Learn how to

This course can help prepare you for the SAS Certified Specialist: Base Programming Using SAS 9.4 and SAS Certified Associate: Programming Fundamentals Using SAS 9.4

Learn how to

In this course Students learn a variety of machine learning and predictive modeling techniques, and how to apply the techniques to big distributed and in-memory data sets. Students also learn about experimentation in business, optimization, and time series forecasting

This self-paced learning is designed for individuals who need a solid foundation in using SAS software to conduct and interpret complex statistical data analysis and who can learn autonomously

The included content helps you prepare for the SAS Certified Statistical Business Analyst Using SAS(R)9: Regression and Modeling credential.

Learn how to

The SAS Customer Intelligence common data model consists of tables that contain information about targeted customers, campaigns, and communications for reporting and follow-up marketing activities

The model also provides operational functionality that maintains real-time customer contact and response history data. For many administrators and users, the common data model is not fully understood. This course demystifies the common data model by presenting an in-depth explanation of its structure, use, and customization.

Prerequisites

The SAS Certified Big Data Professional program represents Level 1 of the SAS Academy for Data Science. Students learn SAS programming skills; introductory statistics; data management and manipulation; data quality techniques, visual data exploration, and how to work with SAS, Hadoop, and Hive

To enrol in the SAS Certified Big Data Professional program, you need at least six months of programming experience in SAS. :

This self-paced learning is designed for individuals who need a solid foundation in using SAS Enterprise Miner and who can learn autonomously. The included content helps you prepare for the SAS Certified Predictive Modeler Using SAS Enterprise Miner 14 credential

This course is for anyone seeking to develop core competency in applied problem-solving with data and statistics. It addresses the Statistical Thinking for Industrial Problem Solving certification exam content areas and tasks.

This self-paced learning is designed for individuals who need a solid foundation in advanced SAS programming techniques and who can learn autonomously. The included content helps you prepare for the SAS Certified Advanced Programmer for SAS(R)9 credential

Advanced SAS eLearning includes below modules

This course provides a review of the majority of topics in the SAS 9.4 Base Programming Performance-Based Exam. It addresses the four exam content areas: Accessing and Creating Data Structures, Managing Data, Generating Reports and Output, and Handling Errors

SAS 9.4 Base Programming Performance-Based Exam Review