Generative AI and Prompt Engineering for Content Design and Multimedia Course

Lesson 1 • AI Content Modalities and Outputs

Maps the landscape of text, image, audio, and video generation. Helps designers choose the right modality for each content goal.

Lesson 2 • How Generative AI Models Work

Covers the core mechanics of large language models and diffusion models without requiring maths. Establishes the conceptual base every later chapter assumes.

Lesson 3 • Ethical and Responsible AI Use

Introduces bias, copyright risk, and transparency obligations relevant to content designers. Frames responsible practice as a professional baseline, not an afterthought.

Lesson 1 • Prompt Patterns and Reusable Templates

Introduces proven prompt patterns such as chain-of-thought, few-shot, and role-play. Templates reduce rework and create consistency across a content team.

Lesson 2 • Iterative Prompting and Refinement

Establishes prompting as a dialogue, not a one-shot command. Students learn systematic iteration cycles to converge on desired outputs efficiently.

Lesson 3 • Anatomy of an Effective Prompt

Breaks a prompt into role, instruction, context, format, and constraint components. Understanding structure is the prerequisite for every advanced technique in this chapter.

Lesson 4 • Clarity, Specificity, and Precision

Teaches how vague language produces vague outputs and how precise wording narrows model behaviour. Students practice rewriting weak prompts into high-specificity versions.

Lesson 1 • AI-Assisted Editing and Rewriting

Uses AI as a structural editor, copy editor, and rewriter rather than a first drafter. Students learn when AI editing adds value and when human judgment must lead.

Lesson 2 • Tone, Voice, and Style Control

Teaches prompts that lock in brand voice, reading level, and emotional register. Style control is essential for content designers serving defined audiences.

Lesson 3 • Content Repurposing and Adaptation

Transforms one source asset into multiple formats—social posts, summaries, scripts—using targeted prompts. Multiplies content output without proportional time investment.

Lesson 1 • Style Consistency Across Visual Assets

Teaches seed values, style references, and prompt templates to maintain visual coherence across a project. Consistency is a core professional requirement for branded content.

Lesson 2 • Instructional Graphics and Diagrams

Focuses on generating diagrams, infographics, and explainer visuals that support learning objectives. Connects visual design decisions to instructional design principles.

Lesson 3 • Evaluating and Curating AI Visuals

Provides a quality rubric for assessing AI images against brief, brand, and audience criteria. Curation skill prevents low-quality visuals from reaching production.

Lesson 1 • Meta-Prompting and Self-Critique Loops

Uses the model to evaluate and improve its own outputs through structured self-critique prompts. Reduces human review cycles on high-volume content production.

Lesson 2 • System Prompts and Persistent Instructions

Teaches how system-level instructions shape model behaviour across an entire session or application. Critical for teams building consistent AI-powered content tools.

Lesson 3 • Retrieval-Augmented Generation Basics

Introduces grounding AI outputs in external documents and knowledge bases to improve accuracy. Relevant for content designers working with proprietary or specialised source material.

Lesson 4 • Prompt Chaining and Sequential Workflows

Connects multiple prompts so each output feeds the next step in a content pipeline. Chaining enables complex deliverables that exceed single-prompt capacity.

Lesson 1 • AI Video Generation and Editing

Introduces AI video generation, scene prompting, and automated editing workflows. Students produce short instructional video segments using AI-assisted production pipelines.

Lesson 2 • Interactive eLearning Content with AI

Uses AI to generate quiz questions, scenario branches, and learner feedback text for eLearning modules. Connects AI output directly to instructional design frameworks.

Lesson 3 • AI Script Writing for Video and Audio

Applies writing prompts to produce narration scripts, explainer video copy, and podcast outlines. Script quality directly determines the effectiveness of all downstream media production.

Lesson 4 • Workflow Integration and Production Pipelines

Maps AI tools to each stage of a multimedia production workflow and identifies handoff points. Efficient pipelines reduce production time while maintaining quality standards.

Lesson 1 • Mapping Content Goals to AI Capabilities

Aligns business and learning objectives with specific AI tool capabilities and limitations. Prevents misapplication of AI to tasks where it adds no value or creates risk.

Lesson 2 • Quality Assurance for AI-Generated Content

Defines review checklists, fact-checking protocols, and editorial standards for AI output. QA processes protect brand credibility and learner trust.

Lesson 3 • Building a Team Prompt Library

Establishes shared prompt repositories, naming conventions, and governance for content teams. A maintained library compounds efficiency gains across every project.

Lesson 1 • Project Brief and Scope Definition

Translates a real-world content challenge into a structured project brief with objectives, audience, and deliverables. Scoping discipline prevents scope creep and ensures measurable outcomes.

Lesson 2 • Review, Refinement, and Final Delivery

Applies QA protocols, peer review, and final editing to bring all assets to delivery standard. The review stage demonstrates professional editorial judgment alongside AI proficiency.

Lesson 3 • Production: Text, Visual, and Media Assets

Executes the planned prompt strategy to generate all written, visual, and multimedia deliverables. Students apply every core skill under realistic production conditions.

Lesson 4 • Prompt Strategy and Asset Planning

Designs the full prompt architecture and asset list before production begins. Planning at this stage prevents costly mid-project pivots and ensures coherent output.