AI Literacy

Living in the AI era

• The rise of AI: What AI really is beyond images and hype

• Meet ChatGPT: How to use its interface in practice

• Is AI a bubble? What bubbles are, past examples, and how to recognize hype vs. lasting innovation

• AI terminology made simple: Generative AI, Large Language Models (LLMs), multimodal AI, tokens, context windows

How AI works

• How LLMs are created: Data collection, tokenization, architecture design, pre-training, fine-tuning, testing, deployment

• Proprietary vs. open-source models: What "parameters" mean, why and how to run models locally, pros, cons, and examples

• Limitations of AI and LLMs: Outdated knowledge, word-by-word generation, fact vs. fiction, hallucinations

Don't let AI overwhelm you

• Recognizing AI vs. human outputs: Why it matters, detection tools, government approaches, and AI-generated text

• Using LLMs for writing: How to collaborate with AI for content creation

• Staying up to date: Model updates, creative use cases, and developments beyond LLMs

Security first

• AI in business contexts: Cybersecurity, agriculture, retail, healthcare

• AI security and compliance: Privacy, intellectual property, and real-world cases

• Legal frameworks for AI: The European AI Act and the US Executive Order on AI

Mindful approach to AI

• Wise use of AI for learning and wellbeing: Avoiding overuse, using AI as a tutor, ChatGPT study mode, boosting motivation

• AI and mental health: Apps, AI as a diary, meditation, risks like sycophancy and "AI psychosis"

• Risks of bias in AI: Stereotyping, human-like biases, and user-driven biases

Introduction to prompt engineering

• AI model landscape: ChatGPT, Claude, Gemini, Grok, Perplexity

• Choosing the right model for your task

• Reasoning vs. non-reasoning models

Prompting strategies

• Prompt roles: System, User, Assistant

• How to engineer a great prompt

• Prompting across different models: OpenAI, Claude, Gemini

Context engineering

• Hallucinations: Why they happen, common types, and how to reduce them

• What context engineering is and why separate chats matter

Advanced AI concepts

• Setting up a project in ChatGPT: Common use cases and best practices

• Advanced concepts: Retrieval Augmented Generation (RAG), context rot, instruction dilution, Model Context Protocol (MCP)

• Designing reusable prompts and custom GPTs

AI productivity tools

• AI for spreadsheets: Gemini in Google Sheets, Excel add-ins, and other AI-powered tools

• AI meeting assistants: Fireflies.ai, Notta.ai

• AI-powered writing: Grammarly vs. LLMs, proofreading workflows, best practices, and common pitfalls

Building websites without coding

• Prototyping with AI: Lovable, Hostinger Horizons, Google Firebase Studio

• AI in coding: When it helps and when it's overused

AI features for automation

• Agent mode of AI: Pros, cons, and ChatGPT as an AI agent

• Automating tasks with AI: Introduction to n8n and how to set it up

• Determining the value of AI features

Image generation

• Creating and editing images with ChatGPT, Gemini, and other AI models

• Writing better prompts for image generation

• Challenges and limitations: Colours, "spillover effects," working with text

• Wider considerations: Impact on creative industries, copyright, licensing, impersonation, and deepfakes

Other multi-modal AI uses

• Voice mode with AI

• Advanced audio generation: Music tools and controversies

Video generation

• AI video models: Veo 3, OpenAI Sora (optional), and others

Capstone Project

• Combine knowledge of text, image, audio, and productivity AI tools into a coherent project

• Design and execute an AI-supported solution for a business or personal challenge

• Present and justify your project outcomes, showcasing understanding of opportunities, risks, and ethical considerations

• Get a personal evaluation and feedback session on your project with an industry professional