Course Content
Lesson 1: What is AI and Why Should I Care?
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Introduction
Learning Outcomes
Key Concepts and Definitions
Theory: How Does AI Work?
Activity – Where Have I Seen AI Today?
Quiz
Reflection Questions
Extension Activity – “My AI Day”
Lesson 2: Can Machines Think Like Me?
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Introduction
Learning Outcomes
Key Concepts and Definitions
Theory: How Do Humans and Machines Think Differently?
Activity – AI vs Human Decision Quiz
Conclusion
Quiz
Reflection Questions
Extension Project – “Human + AI Super Team”
Lesson 3: Train the Machine!
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Introduction
Learning Outcomes
Key Concepts and Definitions
Theory: How AI Learns Like a Student
Activity – Teachable Machine Workshop
Reflection: What Did You Learn?
Conclusion
Quiz
Extension Project – “Smart Classifier Challenge”
Lesson 4: Bias in AI – Is That Fair?
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Introduction
Learning Outcomes
Key Concepts and Definitions
Theory: How Bias Enters AI
Activity – Fair or Unfair?
Conclusion
Quiz
Extension Project – “Fair Tech Pledge”
Lesson 5: Talking to Machines – Natural Language Processing (NLP)
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Introduction
Learning Outcomes
Key Concepts and Definitions
Theory: How Does NLP Work?
Real-Life Examples of NLP
Activity – Talking to Machines
Conclusion
Quiz
Extension Project – “My AI Voice Journal”
Lesson 6: My AI App Idea!
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Introduction
Learning Outcomes
Key Concepts and Definitions
Theory: Designing with Empathy
Activity – AI Assistant Design
Conclusion
Quiz
Extension Project – “AI for Good”
C7: Introduction to AI – Understanding How Machines Learn

By the end of this lesson, students will be able to:

  1. Define Natural Language Processing (NLP) and explain its purpose.

  2. Describe how AI understands human speech or text.

  3. Identify examples of NLP in real life (voice assistants, translators, chatbots).

  4. Recognize the limitations of language-based AI systems.

Reflect on how NLP connects humans and technology.

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