Important Update

Your safety is paramount. Due to COVID-19, upcoming public courses are converting to virtual Live Web classes with a live instructor and virtual labs to practice – just like an in-person class. And, selected Live Web classes in Europe are free. Due to high demand, one free Live Web course registration per individual. Self-paced e-Learning is also available.





SAS Viya

Title Level Training Formats
SAS Viya Enablement Free e-learning
The SAS Viya Enablement training provides access to information about SAS Viya and the related products. This free e-learning provides access to a collection of information, including videos and documentation as well as links to additional product information. This is not a traditional e-learning course.

1 Beginner e-Learning
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
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
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 8.3.

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
Data Preparation on the SAS Viya Open Analytic Platform
This course provides an overview of the analytic data preparation capabilities of SAS Data Preparation on the SAS Viya platform. 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
Advanced Topics in SAS Visual Analytics for SAS Viya 8.4 (8.5) New
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 Classroom
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
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
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
Prepare your data for CAS in 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.

The e-learning includes Virtual Lab time to practice.

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, 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 in detail because of 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 Classroom Live Web Classroom e-Learning
Machine Learning Using SAS Viya
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. 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