Agentic AI - How to with SAS® Viya®
AGAI : AGAIV4
Learn to build, deploy, and monitor Agentic AI LLM-based applications using SAS Viya and the SAS Agentic AI Accelerator.
Learn How To
- Register, publish, deploy, and monitor large language models (LLMs) and Agentic AI workflows (intelligent decision flows).
- Combine proprietary and open-source LLMs with deterministic models in decision-making workflows.
- Govern, version, and scale LLM usage in enterprise applications.
- Configure and use the SAS MCP Server
Who Should Attend
- Technical Roles:
- Data Scientists and AI Engineers
- Cloud Architects
- Developers
- Business Roles:
- Decision Science Professionals
- Mixed Roles:
- Enterprise Application Teams
- AI Strategists
Prerequisites
Before taking this course, you should have an:
- Understanding of LLMs.
- Familiarity with Python for model registration and management.
- Knowledge of:
- SAS Model Manager and ModelOps.
- SAS Intelligent Decisioning.
- SAS Container Runtime.
- Basic deployment techniques (e.g., YAML for Kubernetes, SAS Container Runtime).
- Azure Cloud fundamentals (Azure CLI, cloud concepts).
SAS Products Covered
SAS Intelligent Decisioning;SAS Model Manager
Course Outline
Foundational Model Repository
- Introduction to SAS Foundational Model Repository.
- Standardizing inputs, outputs, and options using Python wrappers.
- Register proprietary and open-source models in SAS Model Manager.
ModelOps - Managing LLMs
- Publish models as Docker images to Azure Container Registry.
- Deploy models to Azure containers using scripts.
- Score deployed models using SAS, Python, or bash scripts.
DecisionOps - Building Agentic AI Workflows
- Create agentic AI workflows with non-deterministic LLMs (e.g., GPT-4o-mini, QWEN) and deterministic models (e.g., gradient boosting).
- Publish and deploy workflows to Azure.
- Score deployed workflows.
Integration with Enterprise Applications
- Integrate workflows into Azure AI Assistants for execution and enhanced functionality.
- Demonstrate integration of Agentic AI workflows into enterprise applications.
Logging and Monitoring
- Learn to collect logs, parse them, and offer a dashboard to monitor LLM usage, performance, responses, and sentiment.
Prompt Builder
- Learn to deploy LLMs to Kubernetes, focusing on secure HTTPS endpoints.
- Configure the SAS Portal for Prompt Builder.
- Create and run prompt experiments with LLMs, save and manifest the best prompt, and deploy it in SAS Model Manager.
- Integrate your prompt with SAS Agentic AI and validate the workflow.
Live Class Schedule
Duration: 10.5 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 coaching 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.
Coaching Services
Take your training to the next level with personalized coaching. While private training offers structured coursework, coaching 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.