Azure AI Agent Service (AI Foundry, Semantic Kernel SDK)

Overview

Are you ready to harness the power of Azure AI Agent Service to build intelligent, scalable, and efficient AI-driven solutions? This comprehensive Udemy course is designed to take you from the fundamentals to advanced implementation, enabling you to develop AI agents that automate tasks, enhance decision-making, and integrate seamlessly into business workflows.

Syllabus

• Introduction to Azure AI Agent Service
Overview of Azure AI capabilities
Understanding AI Foundry and Semantic Kernel SDK
Importance of AI-driven solutions in business
• Fundamentals of AI Agents
Definition and types of AI agents
Key components of an AI agent
Use cases and industry applications
• Setting Up Azure Environment
Creating an Azure account
Navigating the Azure portal
Core Azure AI services and tools
• Introduction to AI Foundry
Features and functionalities of AI Foundry
Configuring AI Foundry for first use
Key integrations and extensions
• Semantic Kernel SDK Basics
Overview of Semantic Kernel SDK
Setting up the SDK environment
Core classes and methods
• Designing AI Agent Workflows
Identifying tasks for automation
Structuring workflows for efficiency
Designing decision-making processes
• Developing AI Agents with Semantic Kernel SDK
Writing basic scripts and implementations
Utilizing SDK classes and methods
Debugging and testing AI agents
• Advanced AI Agent Techniques
Implementing complex decision-making models
Machine learning integration
Enhancing agent intelligence and adaptability
• Integrating AI Agents into Business Workflows
Mapping AI workflows to business processes
Ensuring seamless integration and communication
Monitoring and optimizing AI agent performance
• Scalability and Efficiency Considerations
Best practices for scalable AI solutions
Ensuring high performance and low latency
Security and compliance in AI systems
• Case Studies and Real-world Applications
Analyzing successful AI agent implementations
Lessons learned from industry use cases
Future trends in AI agent development
• Capstone Project
Designing and implementing a full AI agent solution
Presenting and evaluating project outcomes
Feedback and iterating on AI solutions
• Course Conclusion and Next Steps
Reviewing key concepts and skills
Opportunities for further learning and development
Professional pathways in AI agent services

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Taught by

Kuljot Singh Bakshi

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Subjects

Computer Science