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शुरू होता है 5 June 2026 03:47

समाप्त होता है 5 June 2026

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

via Udemy

4160 कोर्स


13 hours 43 minutes

वैकल्पिक अपग्रेड उपलब्ध है

Not Specified

अपनी गति से आगे बढ़ें

Paid Course

वैकल्पिक अपग्रेड उपलब्ध है

अवलोकन

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.

पाठ्यक्रम

  • 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

द्वारा पढ़ाया गया

Kuljot Singh Bakshi


विषय

Computer Science