
Explore the fundamentals of generative AI, including image and text generation with ChatGPT, DALL·E, Stable Diffusion, and MidJourney. Learn best practices and ethical implications.
Discover how generative ai works, using gans for image outputs and transformer models like gpt for text and code generation. Learn to generate images, colorize photos, and code with prompts.
Familiarize yourself with the Udemy user interface to maximize learning, including the course homepage, lecture list, downloadable PDFs, and the bottom tab with overview, Q&A, notes, and learning tools.
Connect with classmates and the instructor through a course-only Facebook group called ChatGPT and GenAI for Content, ask questions, discuss GenAI topics, and access via QR code or Facebook search.
Learn generative AI to automate routine tasks and create content through natural language, unlocking productivity gains and broad use cases in marketing, sales, software engineering, R&D, and customer operations.
Define essential ai terms like llms, generative ai, ai model, neural networks, transformer models, and gans, and explain priming, prompt engineering, ai agents, multimodal llms, model weights, and api-driven inference.
Explore auto-regressive image generation in ChatGPT's GPT-4o, building images left-to-right and top-to-down with strong consistency, inline editing, and prompts that extend existing images, unlike diffusion models.
Explore how generative adversarial networks power narrative images by pairing a generator and discriminator in a feedback loop, enabling text-to-image creation and progressively lifelike results.
Explore how Coca-Cola used Midjourney to create an ad entirely with AI by breaking a video into frames, editing each frame, and recombining them into a coherent video.
Explore how large language models infer the next word from probabilities and prior text, and how prompt engineering and priming unlock practical use while recognizing their hallucinations.
Discover how transformers use attention to power generative AI, from encoding with n-grams to inference driven by prompts, and why LLMs hallucinate.
Explore the basics of prompt engineering as a discipline for designing prompts to harness large language models for tasks like summarization, information extraction, question answering, and code generation.
Explore zero-shot and few-shot prompting, compare their use with LLMs, and learn how examples shape responses, including limitations in complex reasoning and number tasks.
Explore how to evaluate prompts and models using rubrics, inputs, and scores; compare prompts via multiple choice, exact match, and rubric-based open-ended evaluations to iteratively improve prompts.
Apply a framework for writing prompts, covering ten basic parts, including context, tone, background data, detailed task rules, examples, testing, thinking step by step, and output formats for production.
Explore chain of thought prompting to improve math and logical reasoning tasks by having the model show its work, using few-shot and zero-shot prompts with context.
Explore how multimodal LLMs extend transformers with alignment and modality modules to process image, audio, and video tokens, enabling richer prompts, responses, and real-world use cases.
Explore how encoders convert prompts into embeddings and feed decoders to generate text with attention and context weighting.
Explore how retrieval augmented generation enhances LLM responses by combining internal and external sources, improving accuracy, trust, and relevance with private data and cited references.
Generalize your llms knowledge to new chatbots by applying universal prompting principles, including verbose, human-like input, step-by-step thinking, and chain-of-thought prompts, while recognizing hallucinations and domain limits.
Are you ready to move beyond the hype and truly understand the technology that is reshaping the global workforce?
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.
What You Will Learn
Deep Technical Understanding: Demystify complex concepts like Transformers, GANs, Encoders, and Multimodal models.
Prompt Mastery: Move beyond basic inputs with a proven framework for writing powerful prompts, including Chain of Thought and Few-Shot techniques.
Visual Generation: Create high-quality images and video using ChatGPT, Midjourney, and Gemini.
Strategic Application: Analyze case studies (like Coca-Cola) to see how enterprises apply Generative AI.
Future-Proof Skills: Learn about RAG (Retrieval Augmented Generation) and how to evaluate model performance critically.
Who This Course Is For
Professionals looking to integrate AI tools (ChatGPT, Midjourney) into their daily workflows to increase productivity.
Tech Enthusiasts who want to understand the "Under the Hood" mechanics of Transformers and GANs without needing a PhD in math.
Creatives who want to harness AI for image and video generation while understanding the technology behind the art.
Business Leaders who need to decipher the jargon (LLMs, RAG, Multimodal) to make informed decisions.
Enroll today to stop watching the AI revolution from the sidelines and start mastering the tools of tomorrow.