COURSE 11Intermediate8 IN-DEPTH LESSONS

Generative Media

Creative media synthesis: diffusion models, text-to-image architectures, video generation, temporal consistency, audio generation, and authenticity watermarking.

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Course Syllabus & Units

Unit 1

Overview

1 lessons
1.1L1

Generative media overview

**Generative media** means AI systems that create images, audio, video, or other media from prompts or examples—not only classify existing files.

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Unit 2

Images

2 lessons
2.1L1

Diffusion models overview

**Diffusion models** learn to generate images (and other media) by practicing how to remove noise step by step. At generation time they start from noise and denoise toward a picture—often guided by a text prompt.

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2.2L1

Image and video generation

Systems that create **images** and increasingly **video** from prompts, references, or edits—building on diffusion and related generative methods.

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Unit 3

Practice

1 lessons
3.1L1

Prompting for images

Practical patterns for image prompts: subject, composition, style references, negatives, and iteration—plus consent boundaries.

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Unit 4

Video

1 lessons
4.1L1

Video consistency and controls

Making generated video keep identity, motion, and style stable across frames—and giving creators knobs (seed, duration, motion strength, reference frames) without enabling harm.

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Unit 5

Audio

1 lessons
5.1L1

Audio generation overview

Models that generate music, sound effects, or speech audio from prompts or references—sibling to TTS but broader.

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Unit 6

Eval

1 lessons
6.1L1

Evaluation of generative media

How to judge image/audio/video generators: human preference, task fitness, safety filters, and automated proxies with known limits.

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Unit 7

Provenance

1 lessons
7.1L1

Provenance and watermarking overview

Signals and metadata that help people know content may be AI-generated or track origin—watermarks, C2PA-style content credentials, and disclosure norms. None are perfect alone.

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