LangChain Mastery

What you will learn

After finishing this course, you will be able to:

• Engineer an application development project form start to finish.
• Engineer your own solutions by creating a fully functional LLM application.
• Deploy your application to your service of choice (AWS, Google Cloud, Azure, DigitalOcean, Vultr, etc.)

Why choose this course

• Hands-on Projects: Real-world projects from basic to advanced levels ensure you apply what you learn at the end of each module.
• Comprehensive Curriculum: Covers essential to advanced topics, preparing you for various usages.
• Expert Guidance: I will be here to guide you when you get stuck 🙂
• Community Support: Join a private network where I will be replying all your questions.

Hands-on projects

Project 1: A Chatbot with Any LLM

This project covers the fundamentals of language models, prompt templates, chains, and streamlit, along with message schemas.

Project 2: Chatbot FAQ for Any Website

This project involves more advanced concepts such as LCEL, Retrievable Augmented Generation (RAG), retrieval techniques, and vector databases. You'll learn to use LCEL for chaining, explore various retrievers, and use vector stores for similarity searches, culminating in a full-stack Streamlit application.

Project 3: Custom Research Assistant

Build a custom research assistant by understanding and implementing agents and tools. This project distinguishes between agents and chains and teaches you to create your agent.

Deploy Your Apps

Finally, we will deploy deploy our applications. We will cover several ways of doing this, from easy one-click solutions to more advanced deployment pipelines. For the more advanced projects, I will show you how to deploy using git, GitHub, Docker, and CI/CD practices to deploy your apps efficiently and reliably.