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Introduction to Generative AI

Understand how generative models create text, images, audio, and code, what they are genuinely good at, and where their limits and risks begin.

Material Overview
Introduction to Generative AI

Get a clear picture of generative AI without the hype. You will learn how large language models predict text, how diffusion models turn noise into images, and what training, fine tuning, and prompting each contribute to the final result.This E-Learning Material compares leading tools for writing, design, audio, and code, and covers hallucination, licensing, data privacy, and running costs so you can choose the right tool for a specific job.

Curriculum

Learning Path

Each level is enrolled separately. Work through them in order, or start at the level that matches your experience.

  1. Level 01

    Beginner

    Purpose

    Understand what generative AI creates, which tool suits which medium, and where the obvious traps are.

    Outcome

    You can pick the right generative tool for a task and know what to check before using the result.

    What You'll Learn
    • Compare text, image, audio, and code generators and what each is for
    • Learn how a prompt becomes an output in each medium
    • Spot hallucination, style copying, and the limits of free tiers

    150 CREDS

  2. Level 02

    Intermediate

    Purpose

    Look under the surface at how language and image models actually produce their output.

    Outcome

    You can explain why a generative model behaves as it does rather than treating it as magic.

    What You'll Learn
    • Follow how a language model predicts tokens and why it never looks anything up
    • Learn how diffusion models turn noise into an image one step at a time
    • See what training data contributes and why style and bias carry through

    353 CREDS

  3. Level 03

    Advanced

    Purpose

    Combine generative models with your own data and tools so output is grounded rather than invented.

    Outcome

    You can build a generative workflow whose output can be traced back to a source.

    What You'll Learn
    • Add retrieval so answers draw on documents you control
    • Use tool calling to fetch facts, run calculations, and take actions
    • Chain models so one drafts and another reviews or extracts

    665 CREDS

  4. Level 04

    Expert

    Purpose

    Judge generative AI adoption on cost, risk, and quality, and decide what should not be generated at all.

    Outcome

    You can set a generative AI policy that balances value against legal and reputational risk.

    What You'll Learn
    • Model running costs across volume, context length, and model tier
    • Assess copyright, confidentiality, and disclosure obligations for generated material
    • Define quality gates and the tasks where human authorship stays mandatory

    1,018 CREDS