The course equips developers with techniques to enhance the reliability of LLMs, focusing on evaluation, prompt engineering, and fine-tuning. Learn to systematically improve model accuracy through hands-on projects, including building a text-to-SQL agent and applying advanced fine-tuning methods.

A powerful Retrieval Augmented Generation (RAG) application built with NVIDIA AI endpoints and Streamlit. This solution enables intelligent document analysis and question-answering using state-of-the-art language models, featuring multi-PDF processing, FAISS vector store integration, and advanced prompt engineering.

🤖 A modern AI chat assistant powered by Meta's Llama models with real-time web search capabilities, built using React, FastAPI, and Cloudflare AI

This project allows you to convert Llama model weights to the Hugging Face format, making it easier to work with Llama models in various applications.