Lecture 1 : Hello, AI!

• Description: What is AI, and where do we see it every day? We'll define AI in a simple way and explore examples like video games, virtual assistants, and Netflix.
• Project: A group discussion and a fun "AI vs. Me" game to show the difference between human and machine intelligence.

Lecture 2: How Does a Computer "Learn"?

• Description: We’ll introduce the concept of Machine Learning as the way AI learns. The key takeaway is that AI learns from examples, just like we learn from our experiences.
• Project: A hands-on sorting game where students "train" a friend to sort objects based on visual patterns, simulating a basic learning algorithm.

Lecture 3: Meet the "Trainer": Data!

• Description: This class focuses on training data—the examples we give to AI. We'll learn that good data is the most important ingredient for smart AI, and we'll discuss why bad data can cause problems.

Project: A "data detective" activity where students analyze different sets of training data to predict what an AI would learn.

Lecture 4: Become an AI Teacher with Teachable Machine

• Description: Time to get hands-on! We'll use Google's Teachable Machine to train a simple image recognition model. Students will upload images to create different "labels."
• Project: Train an AI to recognize happy and sad faces using their webcams.

Lecture 5: Building with Blocks: Intro to Scratch + AI

• Description: We'll introduce Scratch, a block-based coding platform, and connect our Teachable Machine model to it. This is where we make our AI do something!
• Project: Create a simple Scratch project where a character's animation changes based on the emotion (happy/sad) the AI recognizes from the webcam.

Lecture 6: The AI Rock-Paper-Scissors Challenge

• Description: A fun project to reinforce training and prediction. We’ll train an AI to recognize hand gestures for rock, paper, and scissors.
• Project: Build a fully functional Rock-Paper-Scissors game in Scratch where the player competes against their very own AI opponent!

Lecture 7: The Art of AI: Creative Tools

• Description: AI isn't just for data! We’ll explore how AI can be used to generate art, music, and stories. We'll use a simple text-to-image tool.
• Project: Students will write creative prompts and use an AI image generator to create unique pieces of art.

Lecture 9: AI Music and Sound Recognition

• Description: Explore how AI can "listen" and "make sounds." We’ll use a sound recognition model to control a project.
• Project: Build an interactive project in Scratch where a character dances or changes costumes based on sounds the AI hears (e.g., clapping, snapping).

Lecture 8: The Power of Language: Chatbots!

• Description: We’ll dive into Natural Language Processing (NLP), the field of AI that helps computers understand human language. We’ll build a simple chatbot.
• Project: Create a simple chatbot in Scratch that can hold a conversation and answer questions about a topic like a favorite animal or a video game.

Lecture 10: AI-Powered Smart Home: The Basics

• Description: We'll imagine a smart home and use AI to control it. The focus will be on using sensors (real or virtual) to make decisions.
• Project: Use a virtual motion sensor in Scratch to turn on a virtual light when a person is detected.

Lecture 11: Final Project Planning & Brainstorming

• Description: Students will combine all their skills to plan a final capstone project. They can choose from a list of ideas or come up with their own.
• Project: Develop a plan and a flowchart for their final project, which could be an AI-powered game, a smart home simulation, or a creative tool.

Lecture 12: The Final Project Showcase!

• Description: Students will build and present their final projects, explaining how their AI was trained and how it works.
• Project: Build and present the final project. Example ideas include an AI-powered game that changes levels based on a player's pose, or a "smart recycle sorter" that recognizes different types of waste.