Course Overview
Want to build your own AI assistant using local LLMs? Join me as I develop a practical course on implementing RAG from scratch. You'll learn how to create a complete system that runs on your machine - no cloud services or API costs needed.
Early birds get to follow along as the course takes shape, with access to development livestreams where you can ask questions and participate in building, and get the first look at new content as it's developed. We'll build a minimal but functional end-to-end system, focusing on understanding core RAG concepts through hands-on practice. You'll gain practical experience with vector search, embedding pipelines, and LLM integration.
If you have some Python experience and access to a GPU, this is a fun way to dive into RAG while getting early access at a discounted price.Â
Planned Curriculum
FAQ
What does "local RAG system" mean? This means building a system that runs entirely on a local machine, without relying on external cloud services or APIs.
Do I need a GPU? While a GPU isn't strictly required, the system is likely to be impractically slow without one. I will personally be developing with a local GPU.
Do I need prior experience with AI or machine learning? You should have a basic understanding of LLMs and be comfortable writing and reading code in Python.
What software and tools will I need? I will be developing on a Linux/Ubuntu box and install all required dependencies as required. I do not have access to a Windows machine, and will therefore not be able to provide Windows-specific support.
What is the "Early Bird" special, and how is it different from the final course? Currently the course content does not exist. I will be building it in real-time via livestreams, and then creating more polished videos based on what is created here. The "Early Bird" special gets you access to these livestreams, and first access to the final videos. It will also be half the price of the final course.
Will I have access to the final, polished course content after it's completed? Yes, you will have full and permanent access to all content.
How will the live streams work? When will they be? I do not yet have a specific schedule, but will aim to have 1-2 livestreams most weeks until the content is done. I am in the PST timezone and will primarily stream in the evenings, around 8-11 pm.
What is the expected time commitment for this course? I expect the final (polished) course content to be around 2 hours, but the livestreams to be significantly longer. The amount of time you spend will depend on your goals--i.e., wanting to write every line yourself to learn vs. wanting to just run the provided code.
What kind of support will be available during the course? I will support questions during the livestreams and have a dedicated Discord channel.
What if I can't attend all live sessions? Recordings of livestreams will still be available on YouTube, and sent out to all students.
What is the refund policy for the Early Bird special? The Teachable platform (not my policy!) allows for a full refund for up to 14 days after purchase.
Other Products
Interested in GNNs or getting consulting help? Check out other offerings.
