LangChain and ChatGPT: Build Your Own AI Assistant in 90 Minutes
-
Training TypeLive Training
-
CategoryArtificial Intelligence
-
Duration1 Hours 30 Minutes
-
Rating4,6/5
Course Introduction
About the Course
In this fast-paced, hands-on session, you'll learn how to build a functional AI assistant from scratch using LangChain and ChatGPT. Whether you're a developer, product builder, or AI enthusiast, this course walks you through creating an agent capable of reasoning, responding, and interacting with external tools and APIs. In just 90 minutes, you'll go from zero to having a working assistant that can answer questions, perform tasks, and adapt to your needs—all powered by the latest in language model technology.
Course Objective
By the end of this course, participants will:
Understand the basics of LangChain and how it complements ChatGPT.
Set up a working AI assistant with memory, prompt templates, and tool use.
Integrate external APIs (e.g., search, calculator, file reader) into the agent.
Learn how to use function-calling and chains for structured workflows.
Customize and deploy a basic assistant for personal or professional use.
Who is the Target Audience?
This course is designed for:
Developers and software engineers
Startup founders and product teams
Tech-savvy professionals and makers
Students and hobbyists exploring LLMs and agents
Basic Knowledge
There are no prerequisites for this course.
Available Batches
| 16 Jul 2025 | Wed ( 1 Day ) | Filling Fast12:00 PM - 01:30 PM (Eastern Time) |
| 14 Aug 2025 | Thu ( 1 Day ) | 12:00 PM - 01:30 PM (Eastern Time) |
| 12 Sep 2025 | Fri ( 1 Day ) | 12:00 PM - 01:30 PM (Eastern Time) |
Pricing
Require a Different Batch?
Request a Batch For
-
What is LangChain? Quick overview of core concepts
-
Understanding how ChatGPT + LangChain work together
-
Installing dependencies, API setup (OpenAI + LangChain)
-
Creating a basic LLM-powered assistant
-
Adding prompt templates and conversation memory
-
Making it interactive via terminal or a simple UI
-
Integrating tools (search, calculator, file reader, API caller)
-
Using function calling / agents for dynamic tool selection
-
Hands-on: Build a “Research Assistant” or “Task Bot” with tool use
-
Adding context windows, persistent memory, or database logging
-
Lightweight deployment options (Streamlit, FastAPI, or CLI)
-
Final walkthrough and assistant demo
-
Common issues and debugging tips
-
Resources for further learning
-
Where to go next with LangChain and ChatGPT