Unit Title: Understanding AI: Foundations, Branches, and Basic Definitions
Level: Introductory (Non-technical, Conceptual)
Duration: ~90–120 minutes (flexible self-paced or 2 x 1hr sessions)
🎯 Learning Objectives
By the end of this session, you should be able to:
- Define the concept of artificial intelligence in simple, functional terms.
- Identify the major branches of AI (rule-based, learning-based, adaptive).
- Differentiate between machine learning, NLP, computer vision, and robotics.
- Reflect on where AI appears in your life today.
🧭 Lesson Flow
| Segment | Duration | Format |
|---|---|---|
| 1. Introduction: What Is AI? | 15 min | Script + Discussion/Reflection |
| 2. Branches of AI | 20 min | Guided Explanation + Diagram |
| 3. Key Definitions | 20 min | Micro-lessons with examples |
| 4. AI in the World Today | 15 min | Guided reflection |
| 5. Exercises & Concept Check | 30–45 min | Activities + Outputs |
🧑🏫 1. Introduction: What Is AI?
📖 Teaching Script:
Imagine a machine that helps you write an email. Another that recognises your voice and plays your music. Another that decides whether your loan application is approved. These are all forms of Artificial Intelligence.
At its core, AI is any system that mimics intelligent behaviour — that could mean learning, reasoning, problem-solving, understanding language, or making decisions.
🧠 Conceptual Definition (Working Version):
Artificial Intelligence is the design of systems or software that can perform tasks typically requiring human intelligence — such as recognising speech, understanding language, learning from data, or making decisions.
🧩 2. Branches of AI: The Big Picture
📘 Explanation:
AI isn’t just one thing. It’s a family of techniques. These are the main branches:
| Branch | Description | Example |
|---|---|---|
| Rule-Based AI | Uses predefined rules and logic (IF–THEN) | A thermostat that turns on when it’s below 18°C |
| Machine Learning (ML) | Learns from data rather than being programmed | Email spam filters improving over time |
| Natural Language Processing (NLP) | Understands and generates human language | Chatbots, voice assistants |
| Computer Vision | Interprets visual information | Face recognition in photos |
| Robotics | Uses AI to move and respond in the real world | Self-driving cars, warehouse robots |
🗺️ Activity: Draw a Simple AI Map
- Use a blank page to draw 5 “branches.” Label each one above.
- Under each, add:
- A tool or app you’ve used.
- One real-life problem it could help solve.
📚 3. Key Definitions (Mini-Lesson)
| Term | Explanation | Practical Example |
|---|---|---|
| Algorithm | A set of steps to solve a problem | A recipe, a sorting routine |
| Machine Learning | The ability for machines to learn patterns from data | Spotify recommending songs |
| Neural Network | A structure of learning inspired by the brain | How ChatGPT processes language |
| Training Data | Information used to teach an AI system | Thousands of photos used to teach an app to recognise cats |
| Token | A unit of meaning in a sentence or data stream | In “The sun rises”, the tokens are “The”, “sun”, “rises” |
✍️ Write Definitions in Your Own Words
Use the table above to write your own definitions (2–3 lines each), then write 1 sentence example for each from your life.
🌍 4. AI in the World Today
🔍 Reflection Prompt:
- Where do you see AI right now? List 5 AI systems you’ve interacted with this week (even if you didn’t realise it).
- How does AI affect your decisions, time, or knowledge?
- Is any of it invisible or automatic? Should it be?
🧪 5. Exercises & Concept Check
✅ Exercise 1: Match the Tool to the Branch
Match each tool to its AI branch (you may use the same branch more than once):
| Tool | Branch |
|---|---|
| Google Translate | ? |
| Midjourney (AI art) | ? |
| Siri or Alexa | ? |
| Netflix recommendations | ? |
| Self-driving car | ? |
✅ Exercise 2: Mini Scenario Analysis
Your company wants to build a chatbot that answers FAQs. What kind of AI would this use? What would it need to “learn”?
Write:
- 3 data sources it would need
- 1 risk of getting it wrong
- 1 benefit if it works well
🧠 Knowledge Check (10 Questions):
- What is the simplest definition of AI?
- How is rule-based AI different from machine learning?
- What is an “algorithm”?
- What is a token in language processing?
- Name 3 things AI can do.
- What does “training data” mean?
- Why does AI sometimes make mistakes?
- Name one AI tool you’ve used and what it does.
- What is one way AI helps society?
- What is one danger or ethical issue with AI?
📝 Wrap-Up Assignment (Optional)
Title: “What I Learned About AI This Week”
Write a 300-word reflection answering:
- What surprised you?
- What made sense or connected to your world?
- What do you still want to learn?
📦 End-of-Week Deliverables
- ✅ Completed concept map of AI branches
- ✅ 5–7 key definitions in own words + examples
- ✅ Mini-scenario chatbot case
- ✅ Personal reflection journal or blog entry
- ✅ Answers to the knowledge check