Introducing Azure AI Foundry Agent Service to Scale Your AI Agents - BRK102

Overview

Discover how Azure AI Foundry Agent Service enables scalable AI agent integration, featuring real-world examples from Thermo Fisher's multi-agent system and practical implementation strategies.

Syllabus

• Introduction to the Course
Overview of Azure AI Foundry Agent Service
Course Objectives and Learning Outcomes
• Understanding AI Agents
Definition and Role of AI Agents
Types and Use Cases of AI Agents
• Overview of Azure AI Foundry Agent Service
Key Features and Capabilities
Integration with Azure Cloud Platform
• Scalable Integration of AI Agents
Concepts of Scalability in AI Agents
Benefits of Using Azure AI Foundry for Scaling
• Case Study: Thermo Fisher's Multi-Agent System
Background and Objectives
Architecture and Implementation
Lessons Learned and Best Practices
• Practical Implementation Strategies
Designing AI Agent Architectures with Azure AI Foundry
Deployment and Management of AI Agents
Monitoring and Optimization Techniques
• Hands-On Workshop
Setting Up an AI Agent with Azure AI Foundry
Simulating and Testing Agent Scalability
• Challenges and Solutions
Common Challenges in AI Agent Deployment
Solutions and Troubleshooting Tips
• Future Trends and Innovations
Emerging Trends in AI Agent Technology
Future Directions for Azure AI Foundry
• Conclusion and Next Steps
Recap of Key Concepts
Resources for Continued Learning
Certification and Advancement Opportunities
• Q&A Session
Addressing Participant Queries
Sharing Insights and Experiences

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Subjects

Programming