Develop AI Apps and Agents on Azure (AI-103) Course

Course Code: AI-103

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Duration: 4 days

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Course Overview

Design and build intelligent AI applications and agents on Azure that can reason over text, images and documents. The course focuses on developing AI-infused applications with Microsoft Foundry, including generative AI apps, AI agents, knowledge connections, tools and multimodal capabilities.

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Target Audience

This course is designed for software developers concerned with building, managing and deploying AI solutions that use Microsoft Foundry.

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Course Objectives

• Develop generative AI applications using Microsoft Foundry on Azure.
• Design and implement AI agents capable of task execution and orchestration.
• Build solutions that connect agents to knowledge and tools.
• Work with multimodal AI capabilities and complex content.
• Design scalable, production-ready AI solutions on Azure.

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Course Prerequisites

Participants should be familiar with Python and have knowledge of using APIs and SDKs to build agents and generative AI solutions on Azure.

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Course Content

Module 1: Introduction to AI applications and agents on Azure

• Overview of AI application architectures
• Introduction to generative AI concepts
• Understanding agent-based systems and their role in modern AI
• Overview of Microsoft Foundry capabilities
• Azure services for AI development

Module 2: Developing generative AI applications

• Working with foundation models
• Prompt engineering techniques
• Designing application workflows with generative AI
• Managing inputs, outputs, and context
• Evaluating and refining model responses

Module 3: Building AI agents on Azure

• Agent architecture and design patterns
• Task planning and execution
• Managing agent state and memory
• Event-driven and autonomous agent behaviours
• Debugging and monitoring agent performance

Module 4: Integrating tools and knowledge into agentic solutions

• Tool integration patterns for agents
• Connecting agents to APIs and external services
• Knowledge grounding and retrieval techniques
• Implementing retrieval-augmented generation (RAG)
• Managing data sources and context injection

Module 5: Developing natural language AI solutions

• Natural language processing fundamentals
• Conversational AI design
• Text analysis and classification
• Language generation and summarisation
• Building chat-based interfaces

Module 6: Multimodal AI and complex content understanding

• Working with image and text inputs
• Multimodal model capabilities
• Extracting insights from visual data
• Combining modalities in a single workflow
• Handling complex and unstructured content

Module 7: Building scalable AI solutions with Microsoft Foundry

• Application deployment strategies on Azure
• Scaling AI workloads
• Performance optimisation
• Monitoring and logging
• Security and responsible AI considerations

Module 8: Designing production-ready AI systems

• End-to-end solution design
• Architectural best practices
• Managing lifecycle and updates
• Testing and validation strategies
• Real-world use case scenarios

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Note - This course is delivered via our training partner Global Knowledge.