Learning Paths for Technical Professionals
AI on Azure: LLMs, Foundational Models, & Agents
This starter learning path explores GenAI on Azure, covering LangChain integration, Azure OpenAI, Azure AI Foundry (AI Studio), and Azure AI Agent Service. Learners will build scalable LLM applications, leverage Azure’s cognitive and generative AI services, orchestrate prompt flows, implement RAG, and deploy AI agents using advanced Azure tools and SDKs, while also addressing security, responsible AI, and real-world deployment scenarios.
Learning objectives
- Develop and deploy scalable LLM applications on Azure using LangChain, Azure Cognitive Search, Blob Storage, and PgVector.
- Utilize Azure OpenAI and Azure AI Studio (Foundry) for generative and predictive AI, including prompt engineering, RAG, and multi-modal applications.
- Implement, evaluate, and secure AI solutions with Azure’s content safety, responsible AI practices, and robust authentication and access controls.
- Build, orchestrate, and deploy AI agents using Azure AI Agent Service, integrating function calling, code interpretation, OpenAPI, and knowledge tools.
- Apply Azure SDKs and cloud deployment workflows to automate, containerize, and manage AI projects for real-world business scenarios.
Target audience
This path is designed for AI developers, cloud engineers, data scientists, and technical professionals seeking to master generative AI and agent-based solutions on Microsoft Azure. It is ideal for those with foundational programming skills who want hands-on experience building, deploying, and securing advanced AI applications in enterprise environments.