Online applications are invited for the Short Course on Functions, Tools and Agents with LangChain. Check the details below!
About DeepLearning AI
DeepLearning.AI was founded in 2017 by machine learning and education pioneer Andrew Ng to fill a need for world-class AI education. DeepLearning.AI has created high-quality AI programs on Coursera that have gained an extensive global following. By providing a platform for education and fostering a tight-knit community, DeepLearning.AI has become the pathway for anyone looking to build an AI career.
About LangChain
LangChain is a framework for developing applications powered by language models. We believe that the most powerful and differentiated applications will not only call out to a language model via an API but will also:
- Be data-aware: connect a language model to other sources of data
- Be agentic: Allow a language model to interact with its environment
As such, the LangChain framework is designed with the objective mind to enable those types of applications.
There are two main value props the LangChain framework provides:
- Components: LangChain provides modular abstractions for the components necessary to work with language models. LangChain also has collections of implementations for all these abstractions. The components are designed to be easy to use, regardless of whether you are using the rest of the LangChain framework or not.
- Use-Case Specific Chains: Chains can be thought of as assembling these components in particular ways in order to best accomplish a particular use case. These are intended to be a higher-level interface through which people can easily get started with a specific use case. These chains are also designed to be customizable.
Click here to visit the official website of LangChain
Course Highlights
- Learn about the most recent advancements in LLM APIs.
- Use LangChain Expression Language (LCEL), a new syntax to compose and customize chains and agents faster.
- Apply these new capabilities by building up a conversational agent.
Learning Objectives
The landscape of LLMs and the libraries that support them has evolved rapidly in recent months. This course is designed to keep you ahead of these changes.
You’ll explore new advancements like ChatGPT’s function calling capability, and build a conversational agent using a new syntax called LangChain Expression Language (LCEL) for tasks like tagging, extraction, tool selection, and routing.
After taking this course, you’ll know how to:
- Generate structured output, including function calls, using LLMs;
- Use LCEL, which simplifies the customization of chains and agents, to build applications;
- Apply function calling to tasks like tagging and data extraction;
- Understand tool selection and routing using LangChain tools and LLM function calling – and much more.
Start applying these new capabilities to build and improve your applications today.
Who should join?
Anyone who’s interested in learning about the latest tools to build LLM-based applications. Basic Python knowledge and familiarity with writing prompts for LLMs are recommended.
How to Join?
Interested candidates can directly join through this link.
Instructor
Harrison Chase, Co-Founder and CEO at LangChain
