learn-ai-engineering and awesome-azure-openai-llm
One is a general learning resource for AI and LLMs, while the other is a specialized collection of resources focused on Azure OpenAI, making them complementary for someone learning AI engineering specifically within the Azure ecosystem.
About learn-ai-engineering
ashishps1/learn-ai-engineering
Learn AI and LLMs from scratch using free resources
Organized curriculum spanning mathematical foundations through production deployment, covering machine learning frameworks (scikit-learn, XGBoost), deep learning platforms (TensorFlow, PyTorch), and modern LLM ecosystems including LangChain, LlamaIndex, and Ollama. Includes specialized tracks for computer vision, NLP, reinforcement learning, and agentic AI, plus practical guides for prompt engineering, RAG systems, and MLOps tools like Streamlit and MLflow.
About awesome-azure-openai-llm
kimtth/awesome-azure-openai-llm
A curated collection of resources for 🌌 Azure OpenAI, 🦙 LLMs (RAG, Agents).
The collection organizes resources across five core domains: RAG systems and agentic frameworks (LangChain, LlamaIndex, Semantic Kernel), Azure-native tooling and Copilot integration patterns, LLM research with landscape comparisons and prompt engineering techniques, evaluation benchmarks and LLMOps infrastructure, and production best practices. It emphasizes chronologically-dated entries and concise technical summaries to track rapid ecosystem evolution, particularly focusing on Microsoft's cloud AI stack and agent protocol standards (MCP, A2A, computer use).
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