Build a Custom AI Tiny LLM from Scratch Using PyTorch, A Complete Guide & Chatbot : Bootcamp to create your own ChatGPT from Scratch.
Course Description
Have you ever wondered how ChatGPT, BERT, or other powerful language models actually work? What if you could build your own Tiny Language Model (LLM) from scratch — without using any pre-trained weights, cloud GPUs, or giant datasets?
In this hands-on course, you will learn how to build a complete AI chatbot powered by a transformer-based language model using PyTorch, all from scratch and on your local machine. This course is designed for anyone who wants to truly understand how LLMs work — from data tokenization to training and inference.
You will begin with fundamentals of PyTorch, then build your own TinyGPT model (a simplified GPT-style transformer). You’ll create your own word-level tokenizer, design a training dataset, implement a custom transformer model, train it on CPU, and finally deploy it as an interactive chatbot via CLI and (optionally) a browser UI.
This is not just about running code — you’ll understand the core concepts behind transformers, embeddings, attention, sampling, and text generation, empowering you to build your own AI applications in the future.
By the end of this course, you will have built a real, working AI chatbot powered entirely by your own model — and you’ll truly understand how it works.
Course features:
- Beginner-friendly
- Hands-on coding
- Real-world project
- Pure CPU-based
What Learners Will Build
- A tiny LLM (language model)
- Custom tokenizer (word-level)
- PyTorch model architecture
- Training and inference pipeline
- Interactive chatbot (terminal + web)
- Full understanding of attention, generation, and sampling
- The confidence to build their own domain-specific chatbot
