Learn LangChain, Pinecone & OpenAI: Build Next-Gen LLM Apps
Unleash the Power of AI: Hands-On Applications with LangChain, Pinecone, and OpenAI. Join the AI Revolution Today!
Master LangChain, Pinecone, and OpenAI. Build hands-on generative LLM-powered applications with LangChain. The AI revolution is here and it will change the world! In a few years, the entire society will be reshaped by artificial intelligence. By the end of this course, you will have a solid understanding of the fundamentals of LangChain, Pinecone, and OpenAI.
This LangChain course is the 2nd part of “OpenAI API with Python Bootcamp”. It is not recommended for complete beginners as it requires some essential Python programming experience. Currently, the effort, knowledge, and money of major technology corporations worldwide are being invested in AI. In this course, you’ll learn how to build state-of-the-art LLM-powered applications with LangChain.
What you’ll learn
- How to Use LangChain, Pinecone, and OpenAI to Build LLM-Powered Applications.
- Learn about LangChain components, including LLM wrappers, prompt templates, chains, and agents.
- Learn about the different types of chains available in LangChain, such as stuff, map_reduce, refine, and LangChain agents.
- Acquire a solid understanding of embeddings and vector data stores.
- Learn how to use embeddings and vector data stores to improve the performance of your LangChain applications.
- Deep Dive into Pinecone.
- Learn about Pinecone Indexes and Similarity Search.
- Project: Build an LLM-powered question-answering application for custom or private documents.
- Project: Build a summarization system for large documents using various methods and chains: stuff, map_reduce, refine, or LangChain Agents.
- This will be a Learning-by-Doing Experience. We’ll Build Together, Step-by-Step, Line-by-Line, Real-World Applications.
- You’ll learn how to create web interfaces (front-ends) for you LLM and generative AI apps using Streamlit.
- Streamlit: main concepts, widgets, session state, callbacks.
Recommended LangChain Course