SAS Advanced Machine Learning Subscription

Advanced Modeling Techniques

• COURSE

  Advanced Machine Learning Using SAS® Viya®

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  This course teaches you how to optimize the performance of predictive models beyond the basics by implementing various data munging and wrangling techniques. The course continues the development of supervised learning models that begins in the Supervised Machine Learning Pipelines Using SAS(R) Viya(R) course and extends it to ensemble modeling. Running unsupervised learning and semi-supervised learning models is also discussed. In this course, you learn how to do feature engineering and clustering of variables, and how to preprocess nominal variables and detect anomalies. This course uses Model Studio, the pipeline flow interface in SAS Viya that enables you to prepare, develop, compare, and deploy advanced analytics models. Importing and running external models in Model Studio is also discussed, including open-source models. SAS Viya automation capabilities at each level of machine learning are also demonstrated, followed by some tips and tricks with Model Studio.

  The self-study e-learning includes:
  

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

  
  
  ENROLL

• COURSE

  Deep Learning Using SAS® Software

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  This course introduces the pivotal components of deep learning. You learn how to build deep feedforward, convolutional, and recurrent networks. 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.
  
  ENROLL

• COURSE

  Tree-Based Machine Learning Methods in SAS® Viya®

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  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.

  
  
  ENROLL

• COURSE

  Network Analysis and Network Optimization in SAS® Viya®

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  This course provides a set of network analysis 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.
  
  ENROLL

• COURSE

  Advanced Analytics for IoT Using SAS® Event Stream Processing

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  This course teaches you how to apply advanced analytics techniques to IoT processes. The course addresses analysis of data at rest as well as streaming data. By using the SAS Viya environment with SAS Event Stream Processing, you learn how to deploy your own deep learning models to streaming data.

  The self-study e-learning includes:
  

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

  
  
  ENROLL

• COURSE

  ModelOps: Governing AI and Machine Learning Models That Drive Your Business with SAS®

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  Companies need to continually adapt to changing business conditions. They can make informed decisions with the help of predictive models, but many businesses still struggle with getting models into production in a reasonable timeframe. This course describes how awareness of ModelOps (model operations) can streamline the journey from preparing data, building models, and deploying them in production environments to managing their performance. Proven DevOps (development operations) disciplines are evolving into the unique practice of deploying models in today’s environment.
  Use of SAS Container Runtime and SAS Model Risk Management are also addressed, as are pointers about administrating a production environment.
  This course helps candidates prepare for the SAS Certified ModelOps Specialist exam along with the topics covered in the Managing Models in SAS® Viya® course.
  
  ENROLL

• COURSE

  Generative AI Using SAS®

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  Generative Artificial Intelligence (GenAI) is a rapidly developing area of machine learning, with application across business, government, and academia. In this course, you will learn about different types of GenAI and see examples of how SAS can enhance your efforts to make the most of these techniques.
  
  This course will be released several lessons at a time until all lessons are available. We expect that each lesson can be completed in about an hour, and you can work at your own pace to complete the material. As we release new lessons, you might lose progress through the material that you have completed, so please make a note of where you are leaving off before exiting the course.
  
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