AI Foundations Training

Course

Generative AI Foundations – Diffusion, Attention, and Creative Systems

Course focus:
AI Foundations

Course overview

By the end of this course, students should be able to:

Explain generative AI as a controlled production workflow, not magic.
Describe diffusion in plain language as a learnable denoising process.
Explain why attention helps models connect parts of a prompt, image, or sequence.
Use conditioning, negative constraints, and sampling review to improve outputs.
Evaluate generated media for quality, truthfulness, privacy, rights, and audience impact.

After enrolling, students can complete lesson quizzes as they move through the course.

The course final assessment unlocks after all required lessons and lesson quizzes are complete.

Duration: 3.5 hours
Difficulty: Advanced practitioner foundation
Freshness: Created September 7, 2026 from original daBongo analysis of current website-format AI course references dated 2021 or newer. Verify current tool controls, media policies, and licensing terms before public marketing.

Prerequisites

Practical AI Foundations and basic comfort with modern AI tools. No coding is required, but students should be comfortable with technical concepts.

Tools / Plan Requirements

Any current generative AI assistant for optional practice; a text editor; non-sensitive sample prompts; a personal review checklist.

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