Motivation

This course is about understanding the technology and applying it to build something meaningful. Instead of just learning how LLMs, RAG, LangGraph and agentic AI work in isolation, you’ll see how they come together in the scope of a chatbot proof of concept (PoC). The focus is on making practical decisions, handling real-world challenges, keeping an eye towards production readiness and turning technologies into something functional.

Scope

In this course, we will simulate a scenario where a hypothetical client has requested a chatbot PoC. Our goal is to specify, design, build, and deliver this PoC using LLMs and LangGraph while considering practical constraints and challenges. We will cover project scoping, architecture, implementation, and key factors for production readiness, focusing on what it takes to create a functional and presentable chatbot.

What this course is not

• This is not a beginner-level course. Some exposure to functional and technical aspects of a software engineering project is required to help you get the most out of it.

• This is not a comprehensive LangGraph course, but some basic familiarity will suffice.

Disclaimer

This course is for educational and informational purposes only. The content provided is based on knowledge at the time of creation. While every effort has been made to ensure accuracy, the instructor makes no guarantees, express or implied, about the completeness, reliability, or applicability of the information presented.

Additionally, this course may reference third-party tools, frameworks, or services. These references do not imply endorsement, and the instructor is not responsible for any changes, limitations, or issues related to such external resources.

By enrolling in this course, you acknowledge and agree to these terms.