Generative AI: From Complete Beginner to AI Engineer

About this course

Generative AI for beginners, explained in plain language.

This course gives you a complete map of generative AI. You will learn what a large language model is, how ChatGPT differs from the model behind it, and how an app sends a prompt to an AI API and gets an answer back. You will also learn the ideas behind prompt engineering, retrieval-augmented generation (RAG), AI agents, multimodal image and video models, GPUs, fine-tuning, deployment, and production security.

You do not need a coding background, a math background, an API key, or a paid AI account. Each lecture answers one practical question, shows it on a simple figure, and connects it to the same running example: a small personal assistant. By the end you will be able to follow AI discussions at work, read product claims with a cooler head, and know what a later hands-on course is actually teaching.

What you will understand

You will be able to explain how a model turns a prompt into text, what tokens and a context window are, and why an answer can sound confident and still be wrong. You will be able to tell models, providers, APIs, and applications apart. You will be able to read an AI request and name the endpoint, the JSON body, the model ID, and the credential. You will know how RAG, agents, fine-tuning, and deployment change what an application can do, and which risks matter before that app is shared.

How the course is taught

The lessons are visual and sequential. A new term is defined before it is used. Short Python commands appear only in the Python and RAG lecture, so you can see a terminal, a variable, a virtual environment, and a document split. Everywhere else, the demonstration is a figure, not a pretend live coding session. You can watch on a computer with a browser. Python 3 is optional, and only if you want to type those short examples yourself.

The 12 modules1. Module 1.

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