Introduction to LangChain

Learn to build Software Applications with Large Language Models

REDEEM

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What you'll learn

• Build software applications with Large Language models
• Learn how to augment LLMs with tools and databases
• Learn how to connect LLMs to external data
• Learn the fundamentals of Prompt Engineering
• Learn the fundamentals of Vector Databases
• Learn the fundamentals of Retrieval Augmented Generation
• LangChain: Models, Chains, Prompts, Memory, Vector stores, Agents!

Description

Welcome to the Introduction to LangChain course! Very recently, we saw a revolution with the advent of Large Language Models. It is rare that something changes the world of Machine Learning that much, and the hype around LLM is real! That's something that very few experts predicted, and it's essential to be prepared for the future.

LangChain is an amazing tool that democratizes machine learning for everybody. With LangChain, every software engineer can use machine learning and build applications with it. Prior to LangChain and LLMs, you needed to be an expert in the field. Now, you can build an application with a couple of lines of code. Think about language models as a layer between humans and software. LangChain is a tool that allows the integration of LLMs within a larger software.

Topics covered in that course:

LangChain Basics

Loading and Summarizing Data

Prompt Engineering Fundamentals

Vector Database Basics

Retrieval Augmented Generation

RAG Optimization and Multimodal RAG

Augmenting LLMs with a Graph Database

Augmenting LLMs with tools

How to Build a Smart Voice Assistant

How to Automate Writing Novels

How to Automate Writing Software

The course is very hands-on! We will work on many examples to build your intuition on the different concepts we will address in this course. By the end of the course, you will be able to build complex software applications powered by Large Language Models!

Warning: during the course, I used a lot of the OpenAI models through their API. If you choose to use the OpenAI API as well, be aware that this will generate additional costs. I expect that reproducing all the examples in the course should not require more than $50 in OpenAI credits. However, all the examples can be reproduced for free if you choose to use open-source LLMs.

Who this course is for:

• Intermediate Python developers curious to learn how to develop software applications with Large Language Models
• Machine Learning enthusiasts that want to to improve their knowledge on Large Language Models