Steps for my Career

A practical next path is:

1. Build AI fundamentals first. Start with Introduction to AI in Azure or the Introduction to AI in Azure learning path. These cover core AI concepts, machine learning, generative AI, natural language processing, speech, computer vision, and information extraction.
2. Learn Azure-based generative AI basics. In the Azure learning path, focus especially on:
   • Introduction to generative AI concepts
   • Get started with generative AI in Azure
3. Build Azure AI service knowledge beyond LLMs. An Azure AI engineer is expected to design and implement solutions using Azure AI services, Azure AI Search, and Azure OpenAI, and to handle development, deployment, integration, maintenance, performance tuning, and monitoring.
4. Move toward the Azure AI engineer track. The Microsoft Certified: Azure AI Engineer Associate certification is aligned to building, managing, and deploying AI solutions. It expects experience with Python or C#, REST APIs and SDKs, and building secure solutions for natural language processing, vision, speech, knowledge mining, and generative AI.
5. For agents and RAG specifically, take the applied skills path. The most directly relevant next step is Microsoft Applied Skills: Develop generative AI apps with Azure OpenAI and Semantic Kernel. This credential is focused on developing AI agents by using Azure OpenAI Service and the Semantic Kernel SDK.
6. Strengthen the required coding stack. For the agent-focused applied skills path, familiarity with:
   • Visual Studio Code
   • C# programming
   • Azure OpenAI is expected.
7. Use this learning order.
   • Explore AI basics
   • Introduction to AI in Azure learning path
   • Get started with generative AI in Azure module
   • Microsoft Certified: Azure AI Engineer Associate track
   • Develop generative AI apps with Azure OpenAI and Semantic Kernel

A focused roadmap for the goal of agents and RAG systems is:

• Finish Python basics.
• Complete AI fundamentals in Azure.
• Complete generative AI modules in Azure.
• Learn Azure AI services and Azure AI Search as part of the Azure AI engineer path.
• Move into the applied skills credential for Azure OpenAI and Semantic Kernel to build AI agents.

References:

• Introduction to AI in Azure
• Microsoft Certified: Azure AI Engineer Associate
• Microsoft Applied Skills: Develop generative AI apps with Azure OpenAI and Semantic Kernel
• Explore AI basics