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Generative AI Using SAS®
4h 1m + Hands-On Practice
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Generative AI Using SAS®
GAI : GAI32
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.

New lessons will be added to this course periodically as this field is rapidly developing. 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.
Learn How To
  • Explain what generative AI is and how it fits into the broader AI landscape.
  • Describe several types of GenAI systems.
  • Name some of the key challenges and opportunities in making a trustworthy AI system.
  • Generate synthetic data with Synthetic Minority Oversampling Technique (SMOTE) and Generative Adversarial Networks (GANs).
  • Explain how Large Language Models (LLMs) generate meaningful text.
  • Classify text for LLMs using Bidirectional Encoder Representations from Transformers (BERT).
  • Improve the accuracy and relevance of LLM output using Retrieval Augmented Generation (RAG).
Who Should Attend
Learners who want to know more about the techniques that comprise GenAI and how to make use of them with SAS
Prerequisites
Before taking this course, you should have some background in statistics and machine learning using SAS. You can gain this knowledge by taking the following courses:
  • Statistics You Need to Know for Machine Learning
  • Machine Learning Using SAS Viya
SAS Products Covered
SAS Viya;SAS Machine Learning
Course Outline
Defining Generative AI: Unraveling the Concept
  • Generative AI.
  • The AI landscape.
  • Types of machine learning.
  • Generative models.
  • Generative AI and LLMs.
  • Examples of generative AI technologies.
  • The AI challenge: balancing risk and reward.
  • Generative AI: key takeaways.
Types of Generative AI Systems
  • Generative AI in action.
  • The input-output framework in generative AI.
  • Generative AI systems.
  • Other types of generative AI systems.
Overview of Trustworthy AI and the Analytics Life Cycle
  • Responsible innovation.
  • AI and analytics life cycle.
  • Trustworthy AI: how can SAS help?
  • Data chain of custody.
Transformers and Large Language Models (LLMs)
  • Language models.
  • Sequence models.
  • Attention-based models.
  • Transformer overview.
  • Embeddings.
  • Positional encoding.
  • From transformers to LLMs.
  • GPT-1 and BERT.
  • What is GPT?
  • What is BERT?
  • Comparing GPT-1 and BERT.
  • Timelines.
Synthetic Minority Oversampling Technique (SMOTE) in SAS
  • Separate sampling techniques.
  • What is SMOTE?
  • Demo: understanding SMOTE by using the smoteSample action on a small data set.
  • Demo: Using the smoteSample action to create new cases via SMOTE.
  • SMOTE summary.
Generative Adversarial Networks (GANs) in SAS
  • What are generative adversarial networks (GANs)?
  • Training networks.
  • GANs: advantages and challenges.
  • Applications of GANs.
  • Variants of GANs.
  • Model architecture.
  • Demo: augmenting Data.
  • Synthetic data generation assessment.
  • Comparing GANs and SMOTE.
Classifying Text Using BERT
  • What is BERT?
  • What is BERT used for?
  • Word embeddings.
  • Multi-head attention.
  • Encoding.
  • Multi-head attention details.
  • BERT Pre-training.
  • BERT fine-tuning.
  • SAS Viya VERT text classifier.
  • Demo: Using the BERT text classifier CAS action.
Retrieval Augmented Generation (RAG)
  • Large language models.
  • Retrieval-Augmented Generation (RAG).
  • Supporting documents.
  • RAG pipeline.
  • Demo: Implementing a RAG pipeline, Part 1.
  • Demo: Implementing a RAG pipeline, Part 1.
  • Demo: Implementing a RAG pipeline, Part 2.
  • Demo: Implementing a RAG pipeline, Part 3.
  • Demo: Implementing a RAG pipeline, Part 4.
  • (COMING SOON) Generating SAS Code Automatically with Simple Prompts
  • (COMING SOON) Generating Synthetic Data with No Code/Low Code
Live Class Schedule
Duration: 7 hours
Step into our live classes and experience a dynamic learning environment where you can ask questions, share ideas, and connect with your instructor and classmates. With on-demand lab hours, you can explore the material at your own pace. Our globally acclaimed instructors will motivate you to think bigger, so you can take what you've learned and achieve your biggest goals.
This course isn't publicly scheduled, but private training and mentoring may be available. Contact us to explore options.
Private Training
Get training tailored specifically for your team, led by expert SAS instructors. Choose from virtual sessions, or training at your location (or ours). Perfect for teams seeking a customized curriculum and plenty of interaction with a SAS specialist. We'll schedule it at a time that works for you.
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Mentoring Services
Take your training to the next level with personalized mentoring. While private training offers structured coursework, mentoring provides hands-on, real-time support from a subject matter expert. As you work with your own data, you'll receive expert guidance to help you uncover insights, unlock the full potential of your data, and make faster progress. Perfect for those looking to apply what they’ve learned and see quicker results.
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This course helps prepare you to earn the following SAS Knowledge Badge: