Develop AI apps and agents on Azure (AI-103) (M-AI103)

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