Build Your Own Chatbot with GPT

Course Overview

“Build Your Own Chatbot with GPT” is a course on creating a customized chatbot using the OPENAI API.
Throughout this course, you will learn how to develop a practical and effective chatbot by leveraging cutting-edge techniques such as RAG (Retrieval-Augmented Generation), prompt engineering, and fine-tuning.
The lessons start with fundamental concepts and progress into hands-on practice, where you will program and improve your chatbot step by step.

Understanding GPT Models: Learn the structure and inner workings of GPT and other LLMs
Using the OPENAI API: Familiarize yourself with how to utilize the OPENAI API
Applying RAG: Enhance chatbot performance using Retrieval-Augmented Generation, vector stores, etc.
Prompt Engineering: Master effective prompt-writing techniques to guide your chatbot’s responses
Fine-Tuning: Tackle more challenging problems that can’t be solved by RAG or prompt engineering alone by further training the model
Chatbot UI & Deployment: Build a chatbot user interface and deploy it for real-world use

Open to anyone (no prerequisites required)
Though Python programming is part of the course, Python syntax is covered so that beginners can follow along easily.

Students: Personal laptop, and optionally a payment-enabled credit card
Institution: Classroom (with internet access, HDMI, and projector)
All necessary account setups, power strips, etc., are provided and prepared by AI Castle.

Most chatbots are trained on general data, meaning they don’t include the specific data that companies, institutions, or individuals need.
As a result, a standard GPT model often cannot function as a customized solution for businesses or organizations.
By creating a custom chatbot through this course, you can ensure that your chatbot responds based on the specialized data owned by your company or institution.

You can create a chatbot that has been trained on a company’s internal policies to answer queries about those policies.

chatbot1

You can train a chatbot on novels or other books so that it can provide Q&A based on the content of those books.

chatbot2

This course covers the latest, in-demand advanced techniques for LLMs that are highly sought after in the industry.

Prompt Engineering
- Prompt engineering is one method to guide the chatbot toward the desired type of response.
- You will learn a variety of prompt-engineering skills such as N-shot, in-context, and more, allowing you to create a chatbot tailored to your needs.
RAG (Retrieval-Augmented Generation)
- RAG enables a chatbot to look up the most relevant information to answer a user’s query and generate a response based on that information.
- You will learn various RAG-related techniques, including vector stores and embeddings, to provide customized responses based on user-specific data.
Fine-Tuning
- Further training the model helps solve more difficult tasks that can’t be handled by RAG or prompt engineering alone.
- You will learn how to set hyperparameters and format data for fine-tuning.

This course can be offered in various durations, such as 8 hr, 12 hr, 16 hr, 20 hr, or 24 hr.
The longer the course, the more in-depth content students can explore.