Build, train and deploy your own large language model, step by step, even if you are new to AI.

ChatGPT and its rivals can feel like magic, but every word they produce comes from one simple decision repeated billions of times. This practical audio guide pulls back the curtain and shows you exactly how these models work, and how to build a working one yourself on a laptop or an affordable cloud GPU.

Every technical term is explained in plain language the moment it appears, with clear analogies instead of math-heavy jargon, so you can follow along whether you are a developer, a student or a curious professional.

What you will learn inside:

• How LLMs Really Work: Tokens, embeddings, attention and the transformer architecture, explained so they finally make sense.
• Build Your Own GPT: Set up PyTorch, prepare a dataset, tokenize it and train a small GPT-style model from scratch.
• Train Like the Pros: Loss, learning rates, AdamW, mixed precision, perplexity and scaling laws, with real numbers and real costs.
• Fine-Tune and Align: Turn a raw model into a helpful assistant with instruction tuning, LoRA, QLoRA, RLHF and DPO.
• Deploy It: Sampling, temperature, KV caching, quantization and serving your model with llama.cpp, Ollama or vLLM.

Stop just using AI and start understanding it. By the final chapter, you will know how to build, improve and ship a language model of your own.