HOW TO GET STARTED
Please note that this only serves as a suggested outline to help you get started on the project; it is not mandatory to follow it exactly. Depending on your project, additional steps may be required, or certain steps may be omitted.
Part 1: Getting Started
01
Choose a problem
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Consider thinking about any problems in your daily life or researching other real-world challenges in areas like healthcare, sustainability, accessibility, education, etc.
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Identify what problems AI can help with (e.g., an app that can recognize the ingredients in the fridge and provide a list of possible recipes or an AI-powered chatbot for mental health support).
02
Research and plan your solution
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Outline the goals, key features, how users will interact with them, and how AI plays a part in your project.
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Research and learn about the AI technologies related to your project (e.g., machine learning, computer vision, etc).
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Explore tools like Scratch, App Inventor, Python, etc., to see what fits your project.
03
Select the right tools and applications and start collecting or preparing your data
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Recommended tools and applications, but not limited to:
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Beginners (Ages 8-12): Use Scratch, App Inventor or Thunkable
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Junior (Ages 13-15): Complete as or use App Inventor, Thunkable, web apps, Python, Scikit-Learn or Pandas
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Senior (Ages 16-18): Complete using Python, PyTorch, Numpy, Scikit-Learn, Matplotlib, Seaborn, or Google Colab
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Gather a dataset:
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Public datasets from Kaggle, etc.
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Government sources
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Manually collected data
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If applicable, clean, analyze and format the data.
Part 2: Building Your AI Project
04
Develop and train your AI model
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If using Scratch, App Inventor or Thunkable, integrate AI extensions like speech-to-text, image recognition, etc.
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If using Python, train an AI model with Sciki-Learn or PyTorch based on your chosen problem.
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If applicable, test your models with different datasets and parameters to improve accuracy.
05
Build the User Interface (if applicable)
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Design a simple and intuitive UI if your project involves an app or website.
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Use web apps, Flask or Streamlit to deploy your AI-powered application.
06
Test and improve your project (if applicable)
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Run multiple tests to ensure your AI model works as expected.
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Get feedback and refine your project.
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Fix any bugs or performance issues.
Part 3: Finalization and Submission
07
Create the technical pitch video
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Include the requirements and a demo of your project in the video.
08
Submit your project and other materials based on your division requirements
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Based on your division, submit the other listed materials and documentation
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Double-check the deadlines and ensure your project is completed and your best version before submitting