This AI Makerspace course focuses on building real-world, production-grade applications using large language models (LLMs). It is designed for learners who want to move beyond theory and build scalable AI systems such as Retrieval-Augmented Generation (RAG) pipelines and LLM-powered applications.

The course begins with an introduction to LLM application development, using tools like Hugging Face and Chainlit to create interactive AI systems. Learners are guided through building end-to-end applications that connect models with user interfaces.

A major focus of the course is RAG (Retrieval-Augmented Generation) systems. Learners explore how to enhance LLM performance by connecting them to external data sources for more accurate and context-aware responses.

It then covers advanced frameworks such as LangChain agents and LlamaIndex data agents, showing how to build intelligent systems that can reason, retrieve information, and take actions.

The course also includes production-level engineering topics such as deploying scalable LLM endpoints using Llama 2 and FastAPI.