Explore a comprehensive video tutorial on building a Retrieval QA tool using Langchain, OpenAI, and Faiss, then learn to integrate it with Databricks' MLflow tracking server and model repository. Discover how to create the tool, save components in MLflow, work with model governance, and perform inference after retrieving the chain from the model repository. Access accompanying Jupyter notebooks for hands-on practice in implementing LLMOps techniques with Databricks, enhancing your skills in data science and machine learning.