We’re here to help. As we face COVID-19 together, our commitment to you remains strong. If you want to advance critical, job-focused skills, you’re invited to tap into free online training options or join Live Web classes, with a live instructor and software labs to practice – just like an in-person class.



SAS Viya

Title Level Training Formats
Supervised Machine Learning Procedures Using SAS Viya in SAS Studio
This course combines data exploration, visualization, data preparation, feature engineering, sampling and partitioning, model training, scoring, and assessment. It covers a variety of statistical, data mining, and machine learning techniques performed in a scalable and in-memory execution environment. The course provides theoretical foundation and hands-on experience with SAS Visual Data Mining and Machine Learning through SAS Studio, a user interface for SAS programming. The course includes predictive modeling techniques such as linear and logistic regression, decision tree and ensemble of trees (forest and gradient boosting), neural networks, support vector machine, and factorization machine.

3 Intermediate Classroom Live Web Classroom e-Learning
The Magic of Compelling Reports and Visualizations with SAS

Whether you’re a SAS programmer or a SAS Visual Analytics user, we’ve hand-picked a range of topics to advance your report development and data visualisation skills. With three conference streams to choose from and sessions delivered by our expert trainers, you’ll also have the chance to get hands-on experience, gain extended access to your own SAS environment and try out the techniques you’ve seen.

0 No level Live Web Classroom e-Learning
Summer Fast Track Introduction to Machine Learning
This course is for SAS Viya users who want to work with supervised machine learning models to make better decisions on big data. The training will have 2 main focusses: (1) The preparation of the data to an Analytic Base Table (ABT) and (2) theoretical concepts and the analytical approach of supervised machine learning models.
This training uses different click-and-point tools within SAS Viya. SAS Studio is used to access the data, explore the data, prepare the data; SAS Data Studio to create ABT tables and SAS Model Studio to develop and deploy the model.
This course can help prepare you for the following certification exam(s): SAS Viya 3.4 Supervised Machine Learning Pipelines.

1 Beginner Classroom
Summer Fast Track: Accessible Analytics
This course is for those who are working with big data and want to prepare their data, explore their data, and model their data in a visual way. Results will be presented in an interactive report. SAS Visual Analytics and SAS Visual Statistics are the tools that are used in the training. This fast track combines the courses SAS Visual Analytics 1 for SAS Viya: Basics, SAS Visual Analytics 2 for SAS Viya: Advanced, and SAS Visual Statistics in SAS Viya: Interactive Model Building.

1 Beginner Classroom Live Web Classroom
SAS Platform Administration: Getting Started Free e-learning
This course provides an overview of SAS Viya and SAS 9.4, the SAS Platform.

1 Beginner e-Learning
Machine Learning Leadership and Practice – End-to-End Mastery Business Knowledge Series
  • Accessible to business learners and yet vital to techies as well

  • A vendor-neutral, universally applicable curriculum

  • Equivalent to a full-semester MBA or graduate-level course

Machine learning is booming. It reinvents industries and runs the world. According to Harvard Business Review, machine learning – also known as predictive analytics – is “the most important general-purpose technology of our era.”

But while there are so many how-to courses for hands-on techies, there are practically none that also serve the business leadership of machine learning. This is a striking omission since success with machine learning relies on a very particular project leadership practice just as much as it relies on adept number crunching. Without that leadership, most machine learning projects fail.

By filling that gap, this course empowers you to generate value with machine learning, whether you are a techie, a business leader, or some combination of the two. It delivers the end-to-end expertise that you need, covering both the core technology and the business-side practice.

Why cover both sides? Because both sides need to learn both sides! Everyone leading or participating in the deployment of machine learning must study them both.

Beyond the core tech. As with most machine learning courses, you'll learn how the technical methods work “under the hood” – in an accessible way that's understandable to all learners. But you'll also continue beyond that to master critical business-side best practices that are usually omitted.

1 Beginner e-Learning
SAS Viya Overview
This course provides an introduction to the applications in SAS Viya and discusses how each application is used in each phase of the SAS Analytics Life Cycle: Data, Discovery, Deployment, and Orchestration.

1 Beginner e-Learning
SAS Viya: Overview for Beginners and SAS9 Users
Are you already using elements of SAS 9 and would like to know what innovations and advantages SAS Viya offers?

You know SAS Viya from hearsay and want to get an understanding of the usage and architecture of this modern, cloud-enabled part of the SAS Platform?

This course is aimed at users who want to gain insight into the SAS Viya world in a short time. During the course, you learn the elements of the SAS Viya architecture and SAS Viya applications, create interactive analyses and reports, and get to know the new way of programming with the CAS language. At the appropriate points, the interaction between SAS 9 and SAS Viya, as well as the differences, are discussed.

2 Fundamental Live Web Classroom
SAS Visual Investigator: Building the Interface
This course teaches you how to develop an application interface for monitoring financial crimes.

2 Fundamental Classroom Live Web Classroom e-Learning
System Tuning Using SAS Enterprise Session Monitor
This course is a one-day introduction to SAS Enterprise Session Monitor. SAS Enterprise Session Monitor brings visibility to complex analytic workloads, enabling SAS administrators and developers to keep business-critical SAS servers and applications stable and performing well, control cloud costs, and enable optimal efficiency at scale.

The self-study e-learning includes:

  • Annotatable course notes in PDF format.
  • Virtual lab time to practice.

2 Fundamental Classroom Live Web Classroom e-Learning
SAS Viya and Python Integration for Machine Learning
In this course, you learn to use the Python API to take control of SAS Cloud Analytic Services (CAS) actions from Jupyter Notebook. You learn to upload data into the in-memory distributed environment, analyze data, and create predictive models in CAS using familiar Python functionality via the SWAT (SAS Wrapper for Analytics Transfer) package. You then learn to download results to the client and use native Python syntax to compare models.

3 Intermediate Classroom Live Web Classroom
SAS Viya and R Integration for Machine Learning
In this course, you learn to use the R API to take control of SAS Cloud Analytic Services (CAS) actions from Jupyter Notebook. You learn to upload data into the in-memory distributed environment, analyze data, and create predictive models in CAS using familiar R functionality via the SWAT (SAS Wrapper for Analytics Transfer) package. You then learn to download results to the client and use native R syntax to compare models.

3 Intermediate Classroom Live Web Classroom
SAS Infrastructure for Risk Management: Solution Overview
This course introduces the user to SAS Infrastructure for Risk Management. It covers topics such as job flow instances, job flows, and federated areas.

The self-study e-learning includes:

  • Annotatable course notes in PDF format.
  • Virtual lab time to practice.

3 Intermediate e-Learning
Using SAS Viya REST APIs with Python and R
In this course, you learn to use the R and Python APIs to take control of SAS Cloud Analytic Services (CAS) and submit actions from Jupyter Notebook. You learn to upload data into the in-memory distributed environment, analyze data, and create predictive models on CAS using familiar open-source functionality via the SWAT (SAS Wrapper for Analytics Transfer) package.

3 Intermediate e-Learning
Risk Modeling Add-on for SAS Visual Machine Learning: Using Credit Scoring Nodes
This course provides an overview of the Risk Modeling nodes in SAS Visual Data Mining and Machine Learning. It prepares members of your organization to develop scorecards. The course includes hands-on demonstrations and teaches you key concepts, terminology, and base functionality that are integral to visual risk modeling.

3 Intermediate e-Learning
Network Analysis and Network Optimization in SAS Viya
This course provides a set of network analysis (graph theory) and network optimization solutions using the NETWORK and OPTNETWORK procedures in SAS Viya. Real-world applications are emphasized for each algorithm introduced in this course, including using network analysis as a stand-alone unsupervised learning technique, as well as incorporating network analysis and optimization to augment supervised learning techniques to improve machine learning model performance through input/feature creation.

The self-study e-learning includes:

  • Annotatable course notes in PDF format.
  • Virtual lab time to practice.

3 Intermediate Live Web Classroom e-Learning
High-Performance Data Processing with CASL in SAS Viya
In this course, you learn how to leverage SAS Cloud Analytics Services (CAS), the high-performance, in-memory analytics and distributed computing engine in SAS Viya. You learn how to access, explore, prepare, analyze, and summarize data using the native CAS programming language (CASL). CASL is a new scripting language designed to support the entire analytics life cycle.

3 Intermediate Live Web Classroom e-Learning
Self-Service Data Preparation in SAS Viya
This course provides an overview of the analytic data preparation capabilities of SAS Data Preparation in SAS Viya. These self-service data preparation capabilities include bringing data in from a variety of sources, preparing and cleansing the data to be fit for purpose, analyzing data for better understanding and governance, and sharing the data with others to promote collaboration and operational use.

3 Intermediate Classroom Live Web Classroom e-Learning
Neural Networks: Essentials
This course combines theory and practice to immerse you in the core concepts of neural network models and the essential practices of real-world application. During the course, you programmatically build a neural network and discover how to adjust the model’s essential parameters to solve different types of business challenges. You implement early stopping, build autoencoders for a predictive model, and perform an intelligent automatic search of the model hyperparameter values. The last lesson introduces deep learning. You gain hands-on practice building neural networks in SAS 9.4 and the cutting-edge cloud computing platform for big data analytics, SAS Viya.

3 Intermediate Classroom Live Web Classroom e-Learning
Programming for SAS Viya
This course is for users who need to modify existing Base SAS programs that will execute in SAS Viya. This course leverages the power of SAS Cloud Analytic Services (CAS) to access, manage, and manipulate in-memory tables. This course is not intended for beginning SAS software users.

3 Intermediate Classroom Live Web Classroom e-Learning
SAS Viya Administration: Fast Track
This course is a four-day immersion into a SAS Viya 3.5 environment. This course provides essential topics for SAS Viya 3.5 administration and demonstrates how to perform administration tasks using SAS Environment Manager, the command-line interface, and REST APIs.

The self-study e-learning includes:

  • Annotatable course notes in PDF format.
  • Virtual lab time to practice.

3 Intermediate Classroom Live Web Classroom e-Learning
Machine Learning Using SAS Viya
This course discusses the theoretical foundation for 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. In addition, a business case study is defined to guide participants through all steps of the analytical life cycle, from problem understanding to model deployment, through data preparation, feature selection, model training and validation, and model assessment and deployment. This course is the core of the SAS Viya Data Mining and Machine Learning curriculum. It uses Model Studio, the pipeline flow interface in SAS Viya that enables you to prepare, develop, compare, and deploy advanced analytics models. You learn to train supervised machine learning models to make better decisions on big data.

3 Intermediate Classroom Live Web Classroom e-Learning
Deep Learning Using SAS Software
This course introduces the pivotal components of deep learning. You learn how to build deep feedforward, convolutional, and recurrent networks. The neural networks are used to solve problems that include traditional classification, image classification, and sequence-dependent outcomes. The course contains a healthy mix of theory and application. Hands-on demonstration and practice problems are included to reinforce key concepts. Hyperparameter search methods are described and demonstrated to find an optimal set of deep learning models. Lastly, transfer learning is covered because the emergence of this field has shown promise in deep learning.

3 Intermediate Classroom Live Web Classroom e-Learning
SAS Visual Statistics in SAS Viya: Interactive Model Building
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. This course is appropriate for users of SAS Visual Analytics in SAS Viya.

3 Intermediate Classroom Live Web Classroom e-Learning
SAS Viya Administration
This course is an introduction to the SAS Viya environment. This course provides essential topics for SAS Viya administration and demonstrates how to perform administration tasks using SAS Environment Manager, the command-line interface.

The self-study e-learning includes:

  • Annotatable course notes in PDF format.
  • Virtual lab time to practice.

3 Intermediate Classroom Live Web Classroom e-Learning
Working with SAS Viya Jobs
This course provides information about how to create, design, manage, and run SAS Viya jobs from SAS Studio.
This e-learning course includes virtual lab time to practice.

3 Intermediate Classroom Live Web Classroom e-Learning
High-Performance Data Manipulation with SAS DS2
This course focuses on learning DS2, a fourth-generation SAS language for advanced data manipulation. DS2 blends DATA step and SQL syntax with modern programming structures, and enables parallel processing in Base SAS as well as massively parallel processing environments such as Hadoop and SAS Viya Cloud Analytic Services (CAS). A brief introduction to SAS Viya is included.

4 Expert Classroom Live Web Classroom
Tree-Based Machine Learning Methods in SAS Viya
Decision trees and tree-based ensembles are supervised learning models used for problems involving classification and regression. This course covers everything from using a single tree to more advanced bagging and boosting ensemble methods in SAS Viya. The course includes discussions of tree-structured predictive models and the methodology for growing, pruning, and assessing decision trees, forest models, and gradient boosting models. The course also explains isolation forest (an unsupervised learning algorithm for anomaly detection), deep forest (an alternative for neural network deep learning), and Poisson and Tweedie gradient boosted regression trees. In addition, many of the auxiliary uses of trees, such as exploratory data analysis, dimension reduction, and missing value imputation, are examined, and running open source in SAS and running SAS in open source are demonstrated for tree-based ensemble models.

The self-study e-learning includes:

  • Annotatable course notes in PDF format.
  • Virtual lab time to practice.

4 Expert e-Learning