Design Tasks Around Customization

This project challenges you to go beyond simply following examples. You’ll learn to design and develop your own AI tools to solve real-world problems. The goal is to create custom AI solutions that address specific needs in your school or community.

Learning Objectives

• Solve Real Problems:
  • Identify a real-world issue, like a book recommendation system or predicting traffic congestion.
• Customize AI Solutions:
  • Design a unique AI tool tailored to the problem you choose.
• Develop Practical Skills:
  • Learn how to set up data structures, choose and preprocess data, select the right model, and design a user-friendly interface (UI/UX).
• Build a Prototype:
  • Create a Minimum Viable Product (MVP) using either low-code tools or full-code programming. The MVP doesn’t have to be perfect—it’s a proof of concept that shows your idea works.

Example Activities

1. Defining a Problem:

   • Task: In your team, choose a problem in your school or community.
   • Examples:
     • A system to recommend books in the library based on student interests.
     • A tool to predict and manage traffic congestion around the school.
   • Goal: Clearly define the problem and decide what you want your AI tool to achieve.

2. Customized AI Design:

   • Task: Plan your AI solution.
   • Key Elements:
     • Data Structure & Preprocessing: How will you collect and prepare your data?
     • Model Selection: Which AI model best fits the problem?
     • User Interface (UI/UX): How will users interact with your tool?
   • Activity: Create a design blueprint or flowchart that outlines every step of your AI system.

3. Development & Prototyping:

   • Task: Build your AI tool.
   • Choices:
     • Use a low-code platform (like App Inventor or Power Apps) or write your own code using a programming language (like Python).
     • Focus on creating an MVP—a simple version of your tool that shows it can work.
   • Activity: Develop your prototype, test it with sample data, and make note of any improvements needed.

4. Presentation and Feedback:

   • Task: Present your prototype to your class.
   • Discussion Points:
     • What challenges did you face during design and development?
     • How does your tool solve the problem?
     • What improvements could be made?
   • Goal: Gain feedback to refine your design and learn from your peers.

Key Takeaways

• Customization is Key:
  • Instead of just following examples, you design a tool that addresses a real need.
• End-to-End Process:
  • Learn every step from defining the problem to prototyping your solution.
• Collaboration and Communication:
  • Work with teammates to share ideas, overcome challenges, and improve your project.
• Practical Skills for the Future:
  • Gain hands-on experience in AI design that will help you tackle more complex challenges later on.

By taking on these design tasks, you’ll not only learn how AI works but also how to adapt it creatively to solve problems in your world. Enjoy the process of making your very own AI tool!

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