- Databricks: Large Language Models: Application through Production
- Databricks: Large Language Models: Foundation Models from the Ground Up
- Notes: I'd recommend taking them in this order. The first course provides a good overview of how to build something useful with an LLM. Second course is much more thorough (need to finish)
- Deep Learning Short Courses
- Notes: I've found these really helpful for figuring out how to do something quickly (e.g. get up and running with Langchain) with little filler
- Fast.ai
- Notes: The GOAT for technical people trying to learn AI
- Stanford Artificial Intelligence Professional Program
- Notes: Looks great, not cheap and has some pre-reqs but looks like one of the best online non-grad degree programs. Looks to be directly from Stanford and not any sort of provider (2U, Emeritus, etc.)
- A16z AI Canon
- Notes: Pretty self explanatory, should probabaly read through everything on here
- Large language models, explained with a minimum of math and jargon
- Notes: Probably one of the best blog posts I've ever read on AI. It's both thorough and friendly at the same time. It's a real gut check on your understanding of LLMs. Are you able to articulate these concepts the way this author did?
- Latent Space
- Notes: Good podcast for keeping up with the latest and greatest in AI/LLMs. I particularly like their foundation episodes
- Dwarkesh Podcast
- Notes: Longer form, rapid fire questions with heavy hitter guests (not just AI related but it is a pretty popular topic)
- Demystifing LLMs and Threats
- Notes: Great broad overview of security for LLMs, find myself rewatching it
- Not with a Bug, But with a Sticker: Attacks on Machine Learning Systems and What To Do About Them
- Notes: Very fun, quick, motivating read on security for LLMs
Feel free to contribute to this list by submitting a pull request!