AI For Everyone

• Trace key milestones from the Turing Test to modern generative AI
• Understand what caused the "AI winters" and why AI research stalled at times
• Identify the breakthroughs (data, computing power, deep learning) that triggered today's AI boom
• Connect historical developments to the tools they will use in this course

• Differentiate Narrow AI (ANI), General AI (AGI), and Super AI (ASI)
• Explain why all AI in use today is Narrow AI, including generative tools
• Understand what "generative" means in the context of AI-produced content
• Evaluate realistic expectations versus hype around AGI

• Explain, in non-technical terms, how LLMs predict and generate text
• Understand core concepts like training data, parameters, and tokens
• Recognize why LLMs can be confident and wrong at the same time (hallucination)
• Grasp why the same prompt can produce different outputs across models or runs

• Identify real-world AI applications across at least four industries
• Understand how AI is changing job roles rather than only replacing them
• Recognize opportunities where prompting skills apply directly to their own field
• Evaluate both the benefits and risks of AI adoption in these sectors

Hands-On Exercise: In pairs, list five AI tools already use (knowingly or not) in daily life or work. For each, classify it as Narrow AI, and identify whether it is generative or non-generative.

• Identify the essential elements: clarity, context, constraints, and examples
• Learn to specify tone, audience, and format within a prompt
• Practice writing prompts that reduce ambiguity
• Evaluate prompts against a quality checklist

• Understand what tokens are and how text is measured by the model
• Learn what a context window is and why it limits conversation length
• Recognize symptoms of exceeding a context window (forgetting, truncation)
• Apply strategies to write token-efficient prompts

• Define zero-shot, one-shot, and few-shot prompting
• Identify which approach suits a given task
• Practice converting a zero-shot prompt into a few-shot prompt
• Evaluate trade-offs between prompt length and output quality

• Understand how assigning a role or persona shapes tone and expertise level
• Practice writing persona-based prompts for different professional contexts
• Recognize the limits of persona prompting (it shapes style, not factual accuracy)
• Combine persona with audience targeting for sharper outputs

• Understand what chain-of-thought prompting is and why it improves reasoning tasks
• Practice asking the AI to "think step by step" before answering
• Identify tasks where chain-of-thought helps versus where it adds no value
• Compare direct-answer prompts against step-by-step prompts on the same task

• Request structured outputs like tables, JSON, bullet lists, and headers
• Use conditional instructions ("if X, do Y; otherwise do Z") within prompts
• Understand how structure improves consistency and reusability of AI output
• Practice combining formatting instructions with content instructions

• Understand prompting as an iterative process, not a one-shot task
• Practice A/B comparing two prompt versions for the same goal
• Learn to diagnose why an output failed and adjust the prompt accordingly
• Build a habit of saving and versioning effective prompts

• Recognize prompt injection and manipulation risks
• Understand why sensitive or confidential data should not be pasted into prompts
• Learn basic techniques to reduce hallucinated or unreliable outputs
• Identify red flags that indicate an AI response needs verification

• Understand what prompt chaining is and why complex tasks need it
• Practice breaking a large task into a sequence of smaller prompts
• Recognize how outputs from one prompt can feed into the next
• Explore simple automation concepts (without needing to code)

• Understand the value of maintaining a personal library of reusable prompts
• Practice organizing prompts by category (writing, research, design, etc.)
• Learn to template prompts with placeholders for reuse
• Begin building their own prompt lexicon to use throughout the rest of the course

Hands-On Exercise: Choose one everyday task (e.g., writing a product description). Write three versions of a prompt for it - zero-shot, few-shot, and persona-based with chain-of-thought - run all three, and submit a short comparison of the outputs along with your reasoning for which performed best.

• Structure prompts that generate a coherent long-form outline
• Specify tone, depth, and target reader within a writing prompt
• Practice prompting for introductions, body sections, and conclusions separately
• Learn to prompt for SEO-aware blog content

• Write prompts that generate persuasive, benefit-focused copy
• Specify brand voice, tone, and word-count constraints in prompts
• Practice generating multiple ad variations for A/B testing
• Learn to prompt for different platforms (social ads, email, landing pages)

• Write prompts that establish character, setting, and narrative tone
• Practice guiding plot structure and pacing through prompts
• Explore prompting for different creative formats (dialogue, verse, screenplay)
• Recognize the balance between creative freedom and prompt control

• Write prompts for clear, professional business emails
• Structure prompts for formal reports with sections and summaries
• Practice adjusting tone for different professional contexts (formal, friendly, apologetic)
• Learn to prompt for concise executive summaries

• Practice prompting the AI to revise for tone, length, or clarity
• Learn techniques to make AI text sound more human and personal
• Identify common signs of generic AI writing and how to prompt around them
• Develop a workflow for editing AI drafts into a finished piece

Hands-On Exercise: Pick a real writing task from your own work or studies (a blog post, product description, or email). Draft it using at least three different prompting techniques from this lesson, then revise the best version through a two-round refinement loop, submitting the original prompt, output, and final edited piece.

• Structure prompts using subject, style, lighting, and composition descriptors
• Practice specifying camera angles, lens types, and mood in prompts
• Learn keyword techniques that push outputs toward realism or artistic styles
• Recognize how prompt order and specificity affect image results

• Write prompts that capture brand identity, simplicity, and scalability
• Practice specifying color palettes and style references in prompts
• Understand the limitations of AI tools for vector-based, print-ready logos
• Learn to iterate a logo concept through successive prompts

• Write prompts tailored to platform-specific formats and aspect ratios
• Practice prompting for consistent visual style across a content series
• Learn to incorporate text-safe zones and layout considerations in prompts
• Explore prompting for illustrative versus photographic styles

• Practice using follow-up prompts to modify an existing generated image
• Understand style transfer and how to apply a reference style to new content
• Learn techniques for fixing common AI image errors through prompting
• Build an iterative workflow from rough concept to polished visual

Hands-On Exercise: Choose a fictional or personal brand. Generate a logo concept, one photorealistic image, and one social media graphic for it using at least two different tools. Refine one of the three through at least two rounds of iterative prompting, and submit the prompt history alongside the final visuals.

• Write prompts that generate a logical slide-by-slide outline from a topic
• Practice specifying audience, purpose, and desired number of slides
• Learn to prompt for narrative flow (problem → solution → call to action)
• Adjust prompts to control depth of detail per slide

• Write prompts specifying color themes, fonts, and visual tone
• Practice prompting for consistent branding across a deck
• Learn to request specific slide layouts (comparison, timeline, quote, etc.)
• Understand how to prompt for accessibility-friendly design choices

• Practice prompting for slides that integrate charts, images, and text together
• Learn to describe data visually so the AI generates an appropriate chart type
• Understand how to prompt for image placement alongside key messages
• Build a workflow for assembling a cohesive multi-element slide

Hands-On Exercise: Using a topic of your choice, prompt an AI presentation tool to generate a 6–8 slide deck outline, then refine two slides to include a themed visual layout and one data visualization. Submit the deck along with the sequence of prompts used to build it.

• Write prompts/scripts that specify tone, pacing, and emotion for voiceovers
• Practice formatting text with pauses and emphasis cues for natural delivery
• Learn to match voice style to content type (narration, ad, tutorial)
• Evaluate output quality and identify when a re-prompt is needed

• Write prompts describing genre, mood, tempo, and instrumentation
• Practice generating short background scores suited to a piece of content
• Learn to prompt for specific sound effects using descriptive language
• Understand copyright basics for AI-generated music

• Understand how voice cloning technology works at a conceptual level
• Learn the consent and ethical requirements before cloning any voice
• Practice writing prompts to adjust a cloned voice's tone or emotion
• Recognize responsible-use boundaries for voice cloning tools

Hands-On Exercise: Write a 30-second script for a product or brand, then generate a voiceover using an AI text-to-speech tool with a specific tone and pacing. Pair it with a short AI-generated background score matching the mood, and submit both audio files with the prompts used.

• Practice breaking a script into individual scene-level prompts
• Learn to describe setting, characters, and action clearly for each scene
• Understand how to maintain visual consistency across multiple scenes
• Recognize when a scene needs to be split or simplified for better results

• Write prompts that specify camera angles, movement, and framing
• Practice describing pacing and transitions within a prompt
• Learn to control mood and lighting through descriptive language
• Evaluate generated clips against the intended creative direction

• Understand how to chain prompts across script, voice, and video generation stages
• Practice aligning voiceover timing with generated video scenes
• Learn a basic workflow for assembling a short multi-scene video
• Identify where manual editing is still needed to tie AI outputs together

Hands-On Exercise: Write a short 3-scene script, then generate a video clip for each scene using prompt chaining (script → scene prompt → video). Pair the clips with a voiceover generated in Lesson 6 style, and submit the assembled short video along with your full prompt chain.

• Write prompts that generate accurate, concise summaries of long sources
• Practice specifying summary length, tone, and focus area
• Learn to prompt for comparative summaries across multiple sources
• Recognize when a summary has dropped important nuance

• Write prompts that extract specific data points into structured formats
• Practice requesting tables, lists, or structured JSON from unstructured text
• Learn to prompt for categorization and tagging of extracted information
• Understand strategies for handling large documents within context limits

• Understand why AI research output must always be independently verified
• Practice prompting the AI to cite sources or flag uncertain claims
• Learn manual cross-checking techniques against primary sources
• Recognize common hallucination patterns in research-style outputs

Hands-On Exercise: Select a topic and three source articles. Use AI prompts to summarize each source, extract key data into a structured table, and produce a comparative synthesis. Then manually fact-check three claims from the AI output against the original sources and note any discrepancies found.

• Understand the current legal landscape around AI-generated content ownership
• Recognize copyright risks when using AI-generated text, images, or media commercially
• Learn how to check licensing terms of the AI tools they use
• Identify best practices for attributing or disclosing AI involvement

• Understand what constitutes plagiarism when using AI-generated content
• Learn disclosure practices for academic, professional, and creative contexts
• Practice rewriting AI output to ensure originality where required
• Recognize institutional or platform policies around AI use disclosure

• Identify what types of information should never be entered into AI prompts
• Understand how prompt data may be stored, used, or reviewed by providers
• Learn to configure privacy settings across common AI tools
• Build a personal checklist for safe prompting at work or school

• Understand the purpose and scope of major global AI ethics frameworks
• Identify key principles shared across UNESCO and other responsible-AI guidelines
• Recognize how these guidelines apply to everyday prompting decisions
• Reflect on personal and organizational responsibility in AI adoption

Hands-On Exercise: Take one piece of AI-generated content you created earlier in the course. Write a short responsible-use audit for it covering: potential bias, copyright/ownership risk, disclosure needs, and privacy concerns - then revise the content or your workflow to address at least one identified issue.

• Build a structured prompt log documenting each step of the campaign
• Practice explaining design and prompting decisions clearly for a portfolio audience
• Learn to present before/after iterations to show refinement skill
• Compile a final portfolio piece demonstrating range across the tools covered in the course

Hands-On Exercise (Capstone): Individually or in small groups, plan and produce a multi-format content campaign (e.g., a product launch or awareness campaign) using at least three tools/formats from Lessons 3–7. Submit the final assets alongside a complete prompt log and a short presentation explaining your process, choices, and any responsible-use considerations you addressed.