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Interactive Audio Lesson
Listen to a student-teacher conversation explaining the topic in a relatable way.
Introduction to AI Tools
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Today, we’re introducing tools that you can use to create your own AI models. For instance, Teachable Machine by Google allows you to train a model using images, sounds, or poses. Can anyone tell me what they think a model is?
I think a model is like a representation of something, right?
Exactly! Remember, a model represents patterns that the machine learns from data. Now, can anyone name a type of data we can use?
We can use images, like pictures of different animals!
Yes! Images are a fantastic way to teach a model. As an acronym, let's remember 'PAT' for what you can teach: Patterns, Animals, Text. Now, how do we start training a model?
By collecting sample data!
Correct! Start with selecting your data type, collecting samples, and then we can train the model.
To summarize, we use tools like Teachable Machine to create AI models by selecting data types, collecting samples, and training our model. Make sure to think creatively about the types of data you can use!
Understanding Sustainable Development Goals (SDGs)
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Now, let’s explore how we can apply AI to solve problems related to Sustainable Development Goals. Can anyone suggest a local issue we can work on?
How about air pollution? It’s a big problem in our city.
Great choice! Let's break down our approach using the 4Ws canvas. Who can tell me what the 4Ws are?
Who, what, where, and why!
Exactly! We need to identify who is affected by air pollution. Can anyone share their thoughts?
Local residents, especially kids and elderly people.
Correct! Now, what is the specific problem?
Air pollution from vehicles and factories.
Right! Finally, let's think about why this is a concern.
It can cause health problems for everyone!
Good job! This process helps us understand the details before creating our AI-enabled solutions. Remember the 4Ws as your guide!
Designing an AI-Supported Solution
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Let's brainstorm some features based on what we just learned. If we were to create an AI solution for air pollution, what data points do you think we need?
We could track the vehicle count in our area!
And we should check the air quality index too!
Excellent suggestions! Now, we can use this data to create a system map. System maps help visualize how different data points affect the problem. Has anyone used spreadsheets for data collection before?
Yes! I used Excel for my math project!
Perfect! You can apply those skills here. Remember to visualize your data using graphs to find patterns. It can help us design a smart solution. For instance, what kind of app could we create?
An app that alerts users about pollution levels!
Indeed! Let’s summarize: We discussed how to identify key features, visualize data, and brainstorm potential AI solutions for air pollution. Think about how these concepts connect!
Introduction & Overview
Read a summary of the section's main ideas. Choose from Basic, Medium, or Detailed.
Quick Overview
Standard
In this section, students are equipped with user-friendly tools, such as Teachable Machine and Machine Learning for Kids, to build AI models. They are encouraged to identify real-world problems related to SDGs and propose AI-supported solutions, fostering creativity and critical thinking.
Detailed
Tools to Use
In Chapter 22, titled 'Suggested Projects' for Class 9 on Artificial Intelligence, the importance of hands-on learning is underscored. This section focuses on two primary projects:
- Create an AI Model:
- Students utilize tools like Teachable Machine and Machine Learning for Kids to build AI models. This involves selecting data types (images, text, or sound), collecting sample data, training the model, and testing/refining it. Example tasks include creating image classifiers, sound classifiers, or text classifiers.
- Solving a Problem Related to Sustainable Development:
- This project encourages students to tackle real-world issues aligned with the Sustainable Development Goals. By identifying a local problem (e.g., pollution, water wastage) and using a structured approach like the 4Ws canvas, students explore system maps and data collection through spreadsheets. The aim is to create AI-enabled solutions such as mobile apps or smart systems.
Overall, this section aims to enhance students' practical understanding of AI, boost their problem-solving aptitude, and create awareness about sustainable development through engaging projects.
Audio Book
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Teachable Machine
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- Teachable Machine
Teachable Machine is a web-based tool by Google that allows anyone to train a model using images, sounds, or poses.
Detailed Explanation
Teachable Machine is an accessible tool created by Google that enables users to train AI models easily. It is designed to cater to those without extensive programming knowledge. Users can simply upload images, sounds, or even record their actions to train the AI. This process involves collecting samples of different data types, allowing the model to learn from them and make predictions or classifications based on new input data.
Examples & Analogies
Think of Teachable Machine like teaching a child to recognize different animal sounds. You play the sound of a dog barking multiple times and then ask the child to identify it among other sounds. Just like the child learns by listening, the AI learns from the various inputs it gets through this tool.
Machine Learning for Kids
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- Machine Learning for Kids
Machine Learning for Kids is designed especially for students to create and train models using text, images, or numbers and use them in Scratch or Python.
Detailed Explanation
Machine Learning for Kids is another interactive platform that enables students to dive into machine learning. This tool simplifies the process of creating models with different types of data, such as text, images, or numbers. Once the models are created, students can integrate them into popular programming environments like Scratch or Python, helping them better understand how machine learning can be applied in coding and app development.
Examples & Analogies
Imagine learning to bake a cake. First, you gather all the ingredients (text, images, numbers), then mix them according to a recipe (the model training). Finally, you bake the cake (implementation) and can show it off to others. Similarly, Machine Learning for Kids teaches you all the steps needed to create a functional AI project, just like baking a cake.
Definitions & Key Concepts
Learn essential terms and foundational ideas that form the basis of the topic.
Key Concepts
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Hands-on Learning: Emphasizes using tools for practical application of AI concepts.
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AI Model Training: Involves choosing data, training, and refining models using tools such as Teachable Machine.
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Problem Identification: Understanding local issues through frameworks like the 4Ws Canvas.
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Data Collection: Gathering relevant data points to visualize and analyze problems.
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Sustainable Solutions: Creating AI-driven applications that address sustainable development.
Examples & Real-Life Applications
See how the concepts apply in real-world scenarios to understand their practical implications.
Examples
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Using Teachable Machine to create a model that recognizes different animals based on images.
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Developing a mobile application that provides real-time air quality alerts to users.
Memory Aids
Use mnemonics, acronyms, or visual cues to help remember key information more easily.
🎵 Rhymes Time
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To teach a machine, let’s gather some data, train it well, and watch it progress, ha!
📖 Fascinating Stories
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Once there was a young inventor who used Teachable Machine to create an app that helped reduce pollution in her village. She asked everyone the 4Ws to understand their problems and designed a solution with AI.
🧠 Other Memory Gems
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Remember 'PAT' for what you can teach: Patterns, Animals, Text.
🎯 Super Acronyms
Use 'CATS' for the steps
- Collect data
- Analyze patterns
- Train models
- Share results.
Flash Cards
Review key concepts with flashcards.
Glossary of Terms
Review the Definitions for terms.
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Term: Teachable Machine
Definition:
A web-based tool by Google that allows users to train AI models using images, sounds, or poses.
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Term: Machine Learning for Kids
Definition:
An educational platform that enables students to create and train AI models using text, images, or numbers.
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Term: Sustainable Development Goals (SDGs)
Definition:
A collection of 17 global goals set by the United Nations to address urgent environmental, political, and economic challenges.
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Term: 4Ws Canvas
Definition:
A framework used to understand a problem by asking 'Who,' 'What,' 'Where,' and 'Why.'
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Term: Data Visualization
Definition:
The graphical representation of information and data using visual elements like charts and graphs.