SAS Viya
| Title | Level | Training Formats |
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Introduction to Data Science
The goal of this course is to make analytics approachable and comprehensible. After completing this course, you will be able to perform the main data-related tasks for the citizen data scientist using the point-and-click capabilities of SAS Visual Analytics and SAS Visual Statistics: accessing and manipulating data, exploring data using analytics, and building predictive models. |
1 Beginner |   |
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FDP-Shaping a Data Science Curriculum
This FDP supports developing a data science program that covers a variety of topics and enables students to acquire the skills that industry is looking for their employees to have. The FDP helps universities develop a pool of talent with the range of analytical and technology skills to work in a data-rich business environment. |
1 Beginner | |
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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 | |
Machine Learning Leadership and Practice – End-to-End Mastery 
Presented by Eric Siegel, Ph.D., founder of Predictive Analytics World, author of Predictive Analytics, and former Columbia University professor
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 |  |
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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 | |
SAS Viya Administration: Getting Started 
This course provides an overview of administering SAS Viya. The self-study e-learning includes:
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1 Beginner | |
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Building SAS Studio Flows in SAS Viya
This course is for users who do not have SAS programming experience but need to access and prepare data, and present summarized results. This course focuses on using flows, a point-and-click tool in SAS Studio that visualizes data transformation processes. |
1 Beginner | |
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Getting Started with SAS Workload Management in SAS Viya
This course teaches the fundamentals of SAS Workload Management. |
1 Beginner | |
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Getting Started with SAS and Kubernetes
This course teaches the fundamentals of SAS on Kubernetes. |
1 Beginner | |
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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 | |
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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:
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2 Fundamental | |
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SAS Viya Operations
This course introduces SAS administrators to SAS Viya 2021. This course provides an overview of the new SAS Viya architecture and shows how to perform essential SAS administration tasks like backups, monitoring, and logging using SAS Environment Manager, the command-line interface, Kubernetes, and other open-source applications. The self-study e-learning includes:
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2 Fundamental | |
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SAS Visual Investigator: Building the Interface
This course teaches you how to develop an application interface for monitoring financial crimes. |
2 Fundamental |  |
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Advanced Topics in SAS Visual Analytics for SAS Viya 8.4 (8.5)
SAS Visual Analytics can be used in different ways depending on the company. We have therefore created 8 topics all from our own experience at SAS and how our customers work with our software. You can as a customer put together your own Worksop/Course from the topics below. The material can be used for 2 full days or shorter, depending on your needs. Topics to pick from: Integrate Data Drive Content (2h) During this training we will take a closer look into the Data Driven Content object, which has been available since version 8.2. Data Driven Content object allows you to use 3rd party visualizations/capabilities in SAS Visual Analytics. The benefit is that we no longer are dependent on the default visualizations and capabilities available in SAS Visual Analytics. Advanced Parameters (1h) Parameters are amongst the most powerful and flexible parts of Visual Analytics. During this training we will take a closer look on how to apply advanced techniques on parameters to make VA reports even more flexible. SAS Job execution services (2h) During this training we will take a closer look into SAS Job Execution. You will learn what it is, understand the difference compared with SAS Stored Processes, learn the basics working with SAS Job Execution and how to use SAS Job Execution together with SAS Visual Analytics. Advanced Design (2-3h) Learn tips and tricks to design VA reports.We will discuss best practices and VA specific tips.You will learn layout and design of reports to meet your end-users needs.We’ll discuss the dashboards and data storytelling. Web Integration (1h) SAS Visual Analytics Web SDK is a collection of JavaScript libraries that web developers can use to embed SAS Visual Analytics content within custom web pages and web apps. The SDK provides a framework that enables you to: embed entire reports or individual graph objects from SAS Visual Analytics reports embed graph objects from multiple SAS Visual Analytics reports provide actions between SAS Visual Analytics objects Row level security (1h) Row-level security (RLS) will allow you to build one report and use different data rows from the same dataset for different users.You learn to apply RLS using the Environment Manager and using SAS code and the sas-admin command-line-interface.We will use identity driven properties (userid and group membership), which allow us to make a generic RLS condition for SAS Authenticated users and have it applied based on the properties of the user that uses the report. Load data from DI-studio to CAS and Viya (2h) On this course you will learn how to load data to Viya from SAS Data Integration Studio. We will discuss prerequisites for using DI Studio with Viya, and you will get hands-on using the build-in Cloud Analytics Services Table Loader to load data to Viya. Next, we will look at how to create a custom transformation, if you want more control over the loading of the data to CAS. Advanced calculations (1h) Learn how to use the two Tabular Aggregated functions AggregateCells and AggregateTables. You learn how to create a cumulative total across values of a Category and how to use AggregateTable to perform on-the-fly calculations that were not possible before (like summarizing the salary of employees with-in a departments and afterwards calculating the average total salary at department levels) Import shape-files and use on maps (2-3h) Learn how to import a shape file and create a custom polygon provider so other VA users can draw custom regions with-in the Geomap object. You learn how to inspect the shape file and how to create test data to test the imported shape file. Other topics you can pick from Use the analytical capabilities in VA Suggestions that you are missing |
3 Intermediate | |
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SAS Data Management in SAS Viya 4: Fast Track
In this course, you explore the visual interfaces and learn the programming techniques for loading and preparing your data in SAS Viya. Both the interfaces, SAS Data Preparation (SAS Data Studio) and SAS Studio flows, can be used to create jobs that prepare and load data in CAS. SAS Data Preparation focuses on in-memory data preparation and data wrangling done by the business analyst. SAS Studio flows can be used for other data management use cases like ETL (Extract, Transform, and Load) processing of data on the SAS server where data is first loaded to SAS data sets or a databases before making data available in-memory in CAS. The course also introduces SAS programming techniques to load data in SAS Viya and ways to migrate your Base SAS programs to make use of new capabilities in the DATA step, FedSQL, and procedures to enable fast, parallel in-memory processing in SAS Viya. When explaining the core concepts of data management in SAS Viya, we introduce you to the data architecture of SAS Viya and the CAS data life cycle. CAS IO in SAS Viya introduces you to ways to improve load-processing time using techniques like parallel and multi-node loading. In discussing physical data modeling in CAS, several techniques are discussed to improve the size and performance of in-memory tables. Finally, a discussion of data processing in CAS presents the data manipulation techniques using common procedures, CAS actions, SAS DS2, FedSQL, and data quality algorithms. |
3 Intermediate | |
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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 | |
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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 | |
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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:
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3 Intermediate | |
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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 | |
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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 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 | |
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SAS Health Cohort Builder
This course explores the features and functionality specific to SAS Health: Cohort Builder in SAS Viya 4. Students gain competence in identifying patient cohorts of interest using simple or compound expressions, augmenting the patient cohort data with analysis variables, and leveraging templated analytics to gain knowledge and insights. |
3 Intermediate | |
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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-enabled in-memory analytics engine for big data analytics, SAS Viya. The self-study e-learning includes:
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3 Intermediate | |
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Supervised Machine Learning Procedures Using SAS Viya in SAS Studio
This course covers a variety of machine learning techniques that are performed in a scalable and in-memory execution environment. The course provides hands-on experience with SAS Visual Data Mining and Machine Learning through SAS Studio, a user interface for SAS programming. The machine learning techniques include logistic regression, decision tree and ensemble of trees (forest and gradient boosting), neural networks, support vector machine, factorization machine, and Bayesian networks. The self-study e-learning includes:
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3 Intermediate | |
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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:
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3 Intermediate | |
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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 | |
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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 | |
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Large-Scale Forecasting Using SAS Viya: A Programming Approach
This course teaches students to develop and maintain a large-scale forecasting project using SAS Visual Forecasting tools. For the course project, students build and then refine a large-scale forecasting system. Emphasis is initially on selecting appropriate methods for data creation and variable transformations, model generation, and model selection. Students are then asked to improve overall baseline forecasting performance by modifying default processes in the system. |
3 Intermediate | |
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Developing Custom Steps with SAS Studio Analyst
This course teaches you how to develop custom steps to create a user interface on top of your own code that can be shared, reused, and executed in SAS Studio flows. |
3 Intermediate | |
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SAS Viya Administration Fast Track
This course is a four-day immersion into a 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, and basic Kubernetes commands to administer a SAS Viya environment. The self-study e-learning includes:
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3 Intermediate | |
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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 | |
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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 | |
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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. 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. |
3 Intermediate | |
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Deep Learning Using SAS Software
This course introduces the pivotal components of deep learning. You learn how to build deep feedforward, convolutional, recurrent networks, and variants of denoising autoencoders. 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. Transfer learning is covered because the emergence of this field has shown promise in deep learning. Lastly, you learn how to customize a SAS deep learning model to research new areas of deep learning. |
3 Intermediate | |
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SAS Viya Administration: Fast Track (3.5)
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:
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3 Intermediate | |
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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 | |
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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:
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3 Intermediate | |
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SAS Viya and Python Integration Fundamentals
In this course, you learn to use the SWAT (SAS Wrapper for Analytics Transfer) package to take advantage of the SAS Cloud Analytic Services (CAS) engine in SAS Viya for massively parallel processing (MPP) using familiar Python syntax. You learn about SAS Viya and the CAS engine, how to leverage the strengths of the CAS engine and your local Python client, how to connect Python to CAS, and how to access and load data into CAS's MPP environment. You then learn to explore, analyze, and prepare the data on the CAS server, taking advantage of the distributed processing power using familiar Pandas API and CAS actions from the SWAT package. Lastly, you learn how to return summarized results from the CAS server to your local Python client for additional processing and visualization using native Python packages. |
3 Intermediate | |
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SAS Viya Administration: Enhanced Tasks
This additional topics course expands administrators' knowledge of the SAS Viya 3.5 environment. This course provides additional topics for a SAS Viya 3.5 deployment and shows how to perform advanced administration tasks using SAS Environment Manager, the command-line interface, and REST APIs. The self-study e-learning includes:
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4 Expert | |
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Regression Methods Using SAS Viya
This course covers nine regression methods. The models include linear, logistic, quantile, generalized linear, generalized additive, mixed, survival, nonlinear, and partial least squares. The applications, strengths, and weaknesses of each method are discussed, along with how the methods are implemented in SAS Viya. A comparison of the SAS Viya procedures and SAS/STAT procedures for each method is also shown. Examples in the course show applications in banking, financial services, direct marketing, insurance, telecommunications, medical, and academic fields. The self-study e-learning includes:
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4 Expert | |
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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 | |
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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 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 Tweedy 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. The self-study e-learning includes:
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4 Expert | |