Lesson series

Introduction to Generative AI

This beginner’s course introduces the concepts, models, uses, and ethical considerations of Generative AI, a branch of AI that creates new content such as text, images, audio, code, and video.
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Total Duration

1 Hour

Total Modules

03

Author

Clay Fletcher

Price

FREE

Key Topics Covered

Let's dive into the following aspects of the course right now.

What Generative AI?

AI that generates new data based on learned patterns from large datasets, unlike traditional AI, which classifies or predicts existing data.

Core Model Types:

1: GANs: Competing networks that generate realistic images/videos.

2: Diffusion Models: Create high-quality images by denoising data.

3: Autoregressive Models (Transformers): Predict text tokens step-by-step (e.g., ChatGPT).

4: VAEs: Encode and reconstruct data (useful for face editing, anomaly detection).

5: Flow-Based Models: Produce sharp, controllable, photo-realistic outputs.

How It Works:

Models learn from input–output pairs, recognize patterns, tokenize data, and optimize weights through feedback to generalize beyond memorization.

Application of Generative AI:

Healthcare (drug design), Education (AI tutors), Finance (fraud simulation), Creative fields (art, writing, music).

Tasks:

Automation, decision support, data generation, and content creation.

Limitations & Safe Use:

Risks include bias, misinformation, privacy issues, and ethical challenges (e.g., copyright, misuse).

Safe use involves human oversight, fact-checking, data protection, and ethical transparency.
Author

Clay Fletcher

Clay Fletcher is an AI product specialist with roots in digital design and human-centered computing. After studying at RISD and the University of Maryland, he worked with startups to create intuitive, user-focused AI products. Clay now teaches creators and teams how to integrate AI into design, innovation, and modern content workflows.
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