| File Name: | Demystifying LLMs: Generative AI, RAG & Prompts |
| Content Source: | https://www.udemy.com/course/demystifying-llms/ |
| Genre / Category: | Ai Courses |
| File Size : | 547.0 MB |
| Publisher: | Justin Barnett |
| Updated and Published: | February 20, 2026 |
Welcome to Master Generative AI, a comprehensive journey designed to take you from a curious beginner to a confident practitioner. Whether you are a creative professional, a developer, or a business leader, this course bridges the gap between high-level theory and practical, real-world application. We don’t just show you how to use the tools; we teach you how they work so you can leverage them better than anyone else.
Course Description
Generative AI is not just a trend; it is a fundamental shift in how we interact with information and creativity. But to master it, you need more than just a list of “cool prompts.” You need to understand the architecture that powers these systems.
Section 1: The Foundation We start by cutting through the noise. You will gain a solid command of the terminology and acronyms that confuse most beginners. We explore the “Why” behind the AI boom and set you up for success by ensuring you understand the landscape before diving into the tools.
Section 2: The Visual Revolution (GANs & Video) Next, we dive into the world of AI imagery. You will learn to generate stunning visuals using industry leaders like Midjourney, ChatGPT, and Gemini. But we go deeper—we pop the hood to explore Generative Adversarial Networks (GANs), the technology that started the image revolution. You will also analyze real-world applications through a deep-dive case study on Coca-Cola, examining how major brands are already monetizing this tech.
Section 3: The Brains of AI (LLMs, Transformers & Prompt Engineering) This is the core of the curriculum. We demystify Large Language Models (LLMs) and the Transformer architecture that powers modern AI. You will move past basic chatting and learn the science of Prompt Engineering.
We cover advanced techniques including:
- Zero-Shot and Few-Shot Prompting: How to get results with minimal context.
- Chain of Thought: Teaching the model to “think” before it answers.
- RAG (Retrieval Augmented Generation): Understanding how AI can access external data to provide accurate, up-to-date answers.
- Multimodality & Encoders: How models process text, images, and data simultaneously.
By the end of this course, you won’t just be using AI; you will be evaluating models, writing powerful frameworks for prompts, and understanding the future of this technology.
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