Class 4: Exploring the Magical World of AI & Machine Learning

Course Objectives: ● Understand the basic principles of AI and ML. ● Identify and explore real-world applications of AI and ML. ● Recognize ... Show more
The Kavach
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Course Length: 10 weeks (adjust as needed)

Course Description:
Welcome to an exciting journey where we’ll explore the fascinating world of artificial intelligence (AI) and machine learning (ML)! We’ll discover how computers can learn and make decisions like humans, using exciting examples and activities that spark your curiosity and creativity. By the end of this course, you’ll have a fundamental understanding of AI and ML concepts, develop creative thinking and problem-solving skills, and gain confidence in interacting with AI-powered technologies.

● Participation in class activities and discussions (20%)
● Creative projects and challenges (30%)
● Quizzes and short reflection pieces (20%)
● Final group presentation on an AI application (30%)

Grading Scale:
● A: 90-100%
● B: 80-89%
● C: 70-79%
● D: 60-69%
● F: Below 60%

Teaching Strategies:
● Interactive, hands-on activities that reinforce learning through play and exploration.
● Engaging storytelling and real-world examples to capture interest and imagination.
● Collaborative learning exercises that promote teamwork and critical thinking.
● Open-ended projects that encourage creativity and personalized learning.

Technology Integration:
● Educational coding platforms (e.g., Scratch, Tynker) to create simple AI simulations.
● Age-appropriate online resources and simulations for interactive learning.
● Educational robots or microcontrollers (optional) for advanced explorations.

Special Note:
This syllabus is a suggested framework. Adapt it to suit your teaching style, class dynamics, and available resources. Be open to incorporating student feedback and interests to create a truly engaging and meaningful learning experience.
Chapter-by-Chapter Breakdown:

Chapter 1: What is AI and ML? (Introductory, building towards complexity)
● Introduction to AI and ML concepts in simple terms (using familiar analogies).
● Real-world examples of AI and ML (toys, games, virtual assistants).
● Differentiating between AI and humans (awareness of ethical considerations).
● Hands-on activity: Create a simple “smart” character using physical or digital tools.

Chapter 2: How Do Machines Learn? (Gradual increase in complexity)
● Introduction to different types of data (words, pictures, sounds).
● How machines use data to learn patterns and make predictions.
● Simple coding exercise: Use a visual programming tool to create a pattern-matching program.
● Discussion: Explain the ethical implications of data collection and use in AI systems.

Chapter 3: Robots and Smart Machines (Increasing complexity and hands-on activities)
● Explore different types of robots and their abilities.
● How robots use sensors and actuators to interact with the world.
● Hands-on activity: Build a simple robot using pre-made kits or recycled materials.
● Group project: Choose a real-world robot application and research its benefits and challenges.

Chapter 4: AI in Games and Entertainment (Engaging and relatable topic)
● Discover how AI is used in game design and character behavior.
● Explore virtual assistants and chatbots and how they learn and respond.
● Create a simple AI-powered game or interactive story using a storytelling platform.
● Class discussion: Explore the positive and negative impacts of AI in entertainment.

Chapter 5: AI in Art and Music (Encourages creativity and exploration)
● See how AI is creating art, music, and even writing poetry.
● Hands-on activity: Use an AI-powered tool to create your own art or music piece.
● Brainstorm ethical considerations regarding AI-generated creative content.

Chapter 6: AI in Our Everyday Lives (Connections to personal experiences)
● Identify AI applications in daily life (personalized recommendations, smart homes, etc.).
● Discuss the benefits and potential challenges of AI in various industries.
● Research a specific AI application and present your findings to the class.



Working hours

Monday 9:30 am - 6.00 pm
Tuesday 9:30 am - 6.00 pm
Wednesday 9:30 am - 6.00 pm
Thursday 9:30 am - 6.00 pm
Friday 9:30 am - 5.00 pm
Saturday Closed
Sunday Closed
Class 4: Exploring the Magical World of AI & Machine Learning