Lecture 10 – What is Gen AI & LLM? Model Parameters, Training & Fine-Tuning

Lecture 10 marks the start of the Gen AI portion of our course — after 9 lectures of Python fundamentals, we now dive into the concepts that power tools like ChatGPT, Claude, and Gemini. What we cover in this lecture: What is Gen AI — breaking down "Generative" + "AI," and how any AI model takes an input and produces an output Different generation types: text-to-text, text-to-image, image-to-text, speech-to-text, and more What LLM means — Large Language Model, broken down word by word Understanding model parameters through a simple weighted equation (Y = W1X1 + W2X2 + W3X3) — and why real LLMs scale this to trillions of parameters Clearing up a common confusion: ChatGPT, Claude, and Gemini are chatbots — not the actual LLMs. The real models behind them are GPT-4/5, Claude Sonnet/Opus/Haiku, Gemini Flash/Pro, etc. How LLMs are trained on massive internet-scale text and code data to learn input-output mapping Training vs. fine-tuning — why companies do the heavy full-parameter training, while most practitioners only fine-tune a small portion of an existing model Open source vs. paid/closed source models — what "downloading weights" actually means, using Hugging Face as an example A first look at Ollama for running small open-source models locally (for learning purposes) A preview of upcoming LLM control settings: temperature, max tokens, top-p, top-k, context window (covered in depth next class) Coming up next: A deeper dive into LLM parameters (temperature, top-p, top-k) and prompt/message types. Who this is for: Anyone starting the Generative AI journey — no prior GenAI knowledge needed, though completing the Python module (Lectures 1–9) will help you follow the code examples ahead. Topics/Tags: What is Generative AI, LLM Explained, Large Language Model, Model Parameters Explained, LLM Training vs Fine-Tuning, Open Source LLM, Hugging Face, Ollama, GenAI for Beginners, Learn GenAI 2026 #GenAI #LLM #GenerativeAI #MachineLearning #AITutorial #OpenSourceLLM #LearnAI