AWS and DeepLearning.AI instructors introduce a three-week course on large language models. You'll learn transformer architecture, in-context learning, how to adapt models to your data with RLHF, and write code to build LLM applications.
I'm thrilled to announce this course on Generative AI with Large Language models created by aws and DeepLearning AI. In this three week course you learn in depth how large language models or LLMs really work and how to use them in applications. This course's instructors are Anthea Barth, Chris Fragley, Mike Chambers and Shelby Eigenbro, all of whom work full time on Generative AI at AWS and have supported many companies to build many, many creat applications.
Because LLMs are so new, there's a lot of opportunities for everyone to build applications that just weren't possible before, and this course will give you a deep understanding of how to go about it in detail.
Some of the things that you'll learn are the transformer architecture that powers large language models, a technique called In Context learning, which is key to one shot and few shot prompting, how to adapt models to specific tasks and data sets and also how to align the output of an LLM with human values using RLHF reinforcement learning from human feedback to make it more honest, helpful and harmless.
At the end, you'll have seen or implemented multiple examples of code building and using large language models and you'll come away with a rich intuition about how to use these models yourself. I hope that many of the code snippets you see in this course you also end up being able to directly use in your own work.
So there's a lot to learn and I'm confident you've finished this course with a deeper understanding of how LLMs work and how you can use them. I hope you take this course and use what you learn to build some really cool applications.
