AI & Machine Learning Literacy for Everyone

Level: Beginner-Friendly (No coding required initially)
Duration: 6–8 Weeks | Self-paced
Ideal For: Students, Educators, Professionals, Business Leaders, Policy Makers
Delivery Format: Video Lectures, Case Studies, Worksheets, Visual Aids, Quizzes, Final Assessment
Tools Used: Teachable/Moodle/Google Classroom, Teachable Machine, ChatGPT, Google Colab (optional), AI demos

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Course Objective

To build a well-rounded understanding of Artificial Intelligence and Machine Learning principles, their real-world applications, and the ethical considerations behind them—empowering students to make informed decisions and interact confidently with AI systems.

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MODULE OVERVIEW

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Module 1: What is AI and Why Does it Matter?

Topics Covered:

• Understanding Artificial Intelligence vs Machine Learning vs Deep Learning

• History and Evolution of AI

• Examples of AI in daily life (Google Search, Chatbots, Social Media, Healthcare)

• Myths vs. Reality of AI

Outcome:

Grasp what AI really is, where it is used, and why it’s changing the world.

Activities:

• Watch video case studies: Netflix recommendation, self-driving cars

• Write a short reflection: Where have you used AI unknowingly?

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Module 2: Core Concepts of Machine Learning (ML)

Topics Covered:

• How Machines Learn: Supervised, Unsupervised, Reinforcement Learning

• Algorithms (simplified): Linear Regression, Decision Trees, Clustering

• Datasets, Features, Labels – What they mean

• AI vs Human Learning: Key Differences

Outcome:

Understand how machine learning works without needing to code.

Activities:

• Interactive demo with Teachable Machine or Cognimates

• Use visual simulations to experiment with classification

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Module 3: Data is the New Oil

Topics Covered:

• What is Data? Types of Data (Structured, Unstructured)

• How data is collected, labeled, and cleaned

• Training, Testing, and Validation datasets

• Importance of Big Data in AI

Outcome:

Understand the critical role data plays in AI performance.

Activities:

• Try a simple dataset lab: classifying fruits using Teachable Machine

• Evaluate a fake dataset and spot biases

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Module 4: AI in Real Life – Use Cases by Industry

Topics Covered:

• AI in Education, Healthcare, Finance, Agriculture, Security

• AI in the Creative Industry (writing, design, music)

• Chatbots, Recommendation Engines, Face Recognition, Translation

• Current tools: ChatGPT, DALL·E, AI video generators

Outcome:

Learn how AI is solving real problems and explore tools you can try.

Activities:

• Try ChatGPT to summarize news or write emails

• Explore how AI creates images from text using DALL·E

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Module 5: Bias, Fairness, and Ethics in AI

Topics Covered:

• What is AI bias? How does it happen?

• Examples of unfair AI outcomes

• Why explainability and transparency matter

• Ethical AI Design Principles

• Global perspectives on AI governance and laws

Outcome:

Recognize the social impact and ethical issues around AI systems.

Activities:

• Watch real-world cases: Hiring bias, Face recognition errors

• Class discussion: Who’s responsible for AI mistakes?

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Module 6: Understanding Neural Networks & Deep Learning (Visually)

Topics Covered:

• What is a neural network? (No math)

• How layers work: input → hidden → output

• Deep Learning: Why it’s powerful

• Applications: Speech, vision, translation

Outcome:

Get a high-level visual understanding of deep learning.

Activities:

• Interactive neural network simulator (play with layers and outputs)

• Visual comparison of shallow vs deep learning results

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Module 7: Future of Work & AI Collaboration

Topics Covered:

• Jobs AI can assist, automate, or transform

• Human-AI teaming: not replacement but augmentation

• Skills needed in the AI-powered world (critical thinking, prompt engineering, digital literacy)

• Lifelong learning mindset

Outcome:

Understand how AI impacts careers and how to prepare for it.

Activities:

• Build your AI collaboration plan: Which tasks can AI help you with?

• Career exploration quiz: Which AI-friendly roles suit you?

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Module 8: Getting Hands-On with AI Tools

Topics Covered:

• No-code AI platforms: Google Teachable Machine, Pictory AI, Canva AI, ChatGPT

• Basics of Python & Google Colab (Optional for those interested in coding)

• AI project walkthrough: train a model to recognize images or generate text

Outcome:

Be confident experimenting with AI tools, even without coding experience.

Activities:

• Train your own AI model using Teachable Machine

• Write and refine prompts with ChatGPT for different outcomes

• OPTIONAL: Run a Google Colab notebook for basic ML model

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Final Assessment & Certification

• Final Quiz: Test your understanding across all modules

• Capstone Presentation (optional): Present your understanding of AI’s role in your profession, business, or community

• Certificate: Awarded as “AI Literate: Foundational Certification”

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BONUS MATERIALS

• Downloadable PDF Notes & Infographics for Each Module

• AI Glossary for Beginners (100+ Key Terms)

• AI Tools Directory (Free & Paid)

• Prompt Templates for ChatGPT Use in Education, Business, Marketing

• Lifetime Access to Updates & Case Studies

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TEACHING METHODOLOGY

• Short Video Lectures (5–10 min)

• Slide Presentations with Visual Aids

• Interactive Discussions

• Real-World Case Studies

• Play-based Learning (Experiments with AI Tools)

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TARGET AUDIENCE

• Teachers, students, and parents

• Non-tech professionals (HR, law, finance, etc.)

• Small business owners & entrepreneurs

• Community leaders & policy makers