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Data and AI

Generative AI

Build practical understanding of generative models, prompting, context, retrieval, evaluation, and limitations, then use it for designing reliable AI-assisted workflows for text, images, code, and learning.

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Level
Beginner to advanced foundations
Subject area
Data and AI
Learning outcomes
4 focused outcomes

Topic overview

Learn the foundations of Generative AI.

Generative AI connects generative models, prompting, context, retrieval, evaluation, and limitations with practical decisions and tasks. Guided examples, comparison, practice, and feedback help learners apply these ideas to designing reliable AI-assisted workflows for text, images, code, and learning. The goal is to make each step easier to explain, check, and improve.

Learning outcomes for Generative AI

  1. 1

    Explain the main ideas and vocabulary involved in generative models, prompting, context, retrieval, evaluation, and limitations

  2. 2

    Follow a repeatable process for designing reliable AI-assisted workflows for text, images, code, and learning

  3. 3

    Compare examples, identify common mistakes, and improve an approach

  4. 4

    Complete an independent generative ai task and reflect on the result

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Suggested route

How to learn Generative AI step by step.

01

Build the foundation

Explain the main ideas and vocabulary involved in generative models, prompting, context, retrieval, evaluation, and limitations

02

Practise with feedback

Follow a repeatable process for designing reliable AI-assisted workflows for text, images, code, and learning

03

Practise with feedback

Compare examples, identify common mistakes, and improve an approach

04

Apply and reflect

Complete an independent generative ai task and reflect on the result

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