This course offered by DeepLearning.AI teaches you how to use LangChain to call LLMs to new environments and how to use memories, chains, and agents to take on new and complex tasks.
The course starts with an introduction to LangChain and how it works. It then explores how to use LangChain to call LLMs to new environments. The course also explores how to use memories, chains, and agents to take on new and complex tasks.
The course is designed for developers and data scientists who are interested in learning how to use LLMs for new and complex problems. The course does not require prior knowledge of LLMs or LangChain.
In LangChain for LLM Application Development, you will gain essential skills in expanding the use cases and capabilities of language models in application development using the LangChain framework.
In this course you will learn and get experience with the following topics:
Models, Prompts and Parsers: calling LLMs, providing prompts and parsing the response Memories for LLMs: memories to store conversations and manage limited context space Chains: creating sequences of operations Question Answering over Documents: apply LLMs to your proprietary data and use case requirements Agents: explore the powerful emerging development of LLM as reasoning agents. At the end of the course, you will have a model that can serve as a starting point for your own exploration of diffusion models for your applications.
This one-hour course, instructed by the creator of LangChain Harrison Chase as well as Andrew Ng will vastly expand the possibilities for leveraging powerful language models, where you can now create incredibly robust applications in a matter of hours.