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Introduction to Dec 2023

Welcome to Dec 2023! This course builds upon the concepts learned in Oct 2023 and Nov 2023, introducing more advanced topics and practical applications of LangChain.

What You'll Learn​

In this course, we'll cover:

  1. Docker Introduction: Learn the basics of Docker and how it can be used to containerize LangChain applications. This section covers key Docker concepts and provides a step-by-step guide to creating your first Dockerized Python script.

  2. LangServe on Docker: Discover how to deploy LangChain applications using LangServe in a Docker environment. You'll learn how to set up a development environment, work with LangServe, and follow best practices for Docker-based LangChain development.

  3. Pandas DataFrame Agent: Explore how to use LangChain's DataFrame Agent to interact with Pandas DataFrames using natural language. This section demonstrates how to perform Exploratory Data Analysis (EDA) using simple questions and commands.

  4. RAG (Retrieval-Augmented Generation) Quickstart: Learn about RAG and how to implement it using LangChain for improved language model performance. You'll build a Question Answering system that combines the power of large language models with the ability to retrieve information from specific documents.

  5. Additional Topics: Throughout these sections, we'll also touch on using Google Colab with LangSmith, question-answering using retrievers, and more advanced RAG implementations.

Prerequisites​

Before starting this course, you should have:

  • Completed Oct 2023 and Nov 2023 or have equivalent knowledge
  • Basic understanding of Python programming
  • Familiarity with concepts of large language models and AI

Getting Started​

To begin, make sure you have the necessary environment set up. You'll need Python, LangChain, and potentially Docker installed on your system. Detailed setup instructions will be provided in each section.

Each section in this course is designed to be both theoretical and practical. You'll learn the concepts behind each topic and then apply them in hands-on exercises. By the end of Dec 2023, you'll have a solid understanding of how to use Docker with LangChain, work with advanced agents like the Pandas DataFrame Agent, and implement sophisticated techniques like RAG.

Let's dive in and expand your LangChain knowledge!