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A short class with Sarah and her students. The other ways are under More.
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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!
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!
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!
Emphasizes using tools for practical application of AI concepts.
Involves choosing data, training, and refining models using tools such as Teachable Machine.
Understanding local issues through frameworks like the 4Ws Canvas.
Gathering relevant data points to visualize and analyze problems.
Creating AI-driven applications that address sustainable development.
To teach a machine, let’s gather some data, train it well, and watch it progress, ha!
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.
Remember 'PAT' for what you can teach: Patterns, Animals, Text.
Use 'CATS' for the steps: Collect data, Analyze patterns, Train models, Share results.
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What does Teachable Machine allow you to create?
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What are the four questions in the 4Ws Canvas?
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What problem can you identify to create an AI solution?
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A web-based tool by Google that allows users to train AI models using images, sounds, or poses.
An educational platform that enables students to create and train AI models using text, images, or numbers.
A collection of 17 global goals set by the United Nations to address urgent environmental, political, and economic challenges.
A framework used to understand a problem by asking 'Who,' 'What,' 'Where,' and 'Why.'
The graphical representation of information and data using visual elements like charts and graphs.
This section introduces various tools for creating AI models and solving problems related to Sustainable Development Goals (SDGs), emphasizing hands-on learning for students.
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.
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:
Solving a Problem Related to Sustainable Development:
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.