Udemy – LangChain Mastery:Develop LLM Apps with LangChain & Pinecone 2024-5

Udemy – LangChain Mastery:Develop LLM Apps with LangChain & Pinecone 2024-5 Downloadly IRSpace

Apr 17, 2025 - 20:17 Updated: Apr 21, 2025 - 10:23

0 0

Udemy – LangChain Mastery:Develop LLM Apps with LangChain & Pinecone 2024-5

LangChain Mastery:Develop LLM Apps with LangChain & Pinecone, Master LangChain, Pinecone, OpenAI and Google’s Gemini. Build hands-on generative LLM-powered applications with LangChain. Create powerful web-based front-ends for your generative apps using Streamlit. 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, OpenAI and Google’s Gemini Pro and Pro Vision. You’ll also be able to create modern front-ends using Streamlit in pure Python. 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. In this course, we’ll go over LangChain components, LLM wrappers, Chains, and Agents. We’ll dive deep into embeddings and vector databases such as Pinecone. This will be a learning-by-doing experience. We’ll build together, step-by-step, line-by-line, real-world LLM applications with Python, LangChain, and OpenAI. The applications will be complete and we’ll also contain a modern web app front-end using Streamlit. We will develop an LLM-powered question-answering application using LangChain, Pinecone, and OpenAI for custom or private documents. This opens up an infinite number of practical use cases.

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 using multimodal Google’s Gemini Pro Vision
How to integrate Google’s Gemini Pro and Pro Vision AI models with LangChain
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 app with a modern web-based front-end 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.

Who this course is for

Python programmers who want to build LLM-Powered Applications using LangChain, Pinecone and OpenAI.
Any technical person interested in the most disruptive technology of this decade.
Any programmer interested in AI.