Resources

Introduction

Welcome to the USAII Global AI Hackathon resource hub! Whether you're new to AI or experienced, these resources will help you prepare for the qualifier, build your project, and create a compelling submission.

Challenge Briefs

  • High School Track: [Link to Data Full Challenge Brief]
  • Undergrad Track: [Link to Data Full Challenge Brief]
  • Graduate Track: [Link to Data Full Challenge Brief]

 

Getting Started

Preparing for the Qualifier

  • USAII Bootcamp: https://aihackathon.usaii.org/ai-bootcamps
  • Qualifier Prep Guide: [ADD LINK]
  • Attend USAII Global AI Builder series (June 7 - 20) (Discord: #usaii-global-ai-builder-series)
    • The Future of AI Innovation
    • From Problem → AI Solution
    • Responsible AI Design
    • AI Tools for Rapid Prototyping
    • Current AI landscape
    • AI System Architecture Basics
    • Designing AI Products
    • How to Build a Winning Hackathon Project
    • Pitching Your AI Idea
    • AI Careers & Hiring Signals
    • Sponsor Innovation Spotlight
    • High School: AI Foundations
    • Undergraduate: AI Foundations
    • What judges look for in winning project

Planning Your Build

Before you start building, take time to think clearly about your solution.

Step 1 — Define the Problem

  • Who are you helping?
  • What decision or action are you improving?
  • Why does this problem matter?

Resource: https://www.designkit.org/methods/how-might-we

Step 2 — Decide if AI is Appropriate

Not every problem needs AI.

Ask:

 

  • Does this involve patterns, predictions, or language?
  • Would a simple system work just as well?

Step 3 — Design Your AI System

Think in this structure:

  • Input: What data goes in?
  • AI Layer: What model or logic is used?
  • Output: What does the user receive?

Step 4 — Keep It Simple

Most winning projects:

  • Solve one clear problem
  • Use AI appropriately (not excessively)
  • Demonstrate value clearly

 

Tools & Technologies

 

You are NOT required to use any specific tools. Choose what fits your idea.

AI Platforms & Models

Development Platforms

No-Code / Low-Code AI

Data & Visualization

 

  • Pandas
  • Matplotlib / Seaborn
  • Plotly
  • Tableau Public

Collaboration

 

Development Tools

Version Control

  • GitHub – Code hosting and collaboration at github.com
  • Git – Version control system

 

Working with Data 

 

  • Public datasets
  • Simulated data
  • Synthetic data

Creating Synthetic Data

You must:

  • Explain how it was generated
  • Justify why real data wasn’t used
  • Ensure it is realistic

Tools for Synthetic Data

Free Dataset Sources

 

How to Win 

What Judges Look For

1. Problem Clarity
  • Is the problem clearly defined?
  • Is it meaningful?
2. AI Appropriateness
  • Is AI actually needed?
  • Is it used correctly?
3. Solution Design
  • Is the system well thought out?
  • Does it make sense technically?
4. Impact
  • Does it help real people?
  • Is it useful?
5. Responsibility

 

  • Are risks considered?
  • Is the system safe and ethical? 

 

Contact Us & Support Channels

Discord Community

  • Discord: https://discord.gg/ePjenJnyh4
  • Real-time Q&A
  • Team formation
  • Technical troubleshooting
  • Mentor connections
  • Event update

  • Key Channels: 
    • #help-desk – General questions
    • #team-formation – Find teammates
    • #qualifier-prep – Qualifier support
    • #high-school-track – HS-specific discussion
    • #undergraduate-track – Undergrad discussion
    • #graduate-track – Graduate discussion
    • #tech-support – Tech troubleshooting

  • Mentor Office Hours
    • Schedule: Available in Discord #office-hours

  • Three Time Zone Bands:
    • Americas: 10 AM-12 PM ET, 6-8 PM ET
    • EMEA: 10 AM-12 PM GMT, 5-7 PM GMT
    • APAC: 10 AM-12 PM IST/SGT, 5-7 PM IST/SGT

Email Support

 

Common Issues & Solutions

  • Can't access qualifier?
    Email qualifier.hackathon@usaii.org with subject "Qualifier Access Issue" and your Team ID

  • Discord verification not working?
    Check #tech-support channel for verification bot instructions

  • Submission form errors?
    Screenshot error + post in #tech-support with your Team ID

  • Video upload issues?
    Upload to YouTube/Vimeo/Loom, paste link (don't upload directly to Devpost)

  • Demo link broken?
    Test in incognito browser before submitting

 

Additional Resource Links 

AI & ML Learning

  • Fast.ai – Practical deep learning courses at fast.ai
  • Google AI – Machine learning crash course at developers.google.com/machine-learning
  • Kaggle Learn – Free micro-courses at kaggle.com/learn
  • Elements of AI – Free AI basics at elementsofai.com
  • Andrew Ng's ML Course – Coursera machine learning

Responsible AI

As part of this hackathon, you are expected to design thoughtful and responsible AI solution. We encourage you to review:

  • Responsible AI Framework – https://www.microsoft.com/en-us/ai/responsible-ai
  • Data Privacy for Students – https://www.commonsense.org/education/articles/what-is-data-privacy
  • Avoiding Bias in AI Systems – https://developers.google.com/machine-learning/fairness-overview
  • AI Ethics Guidelines – https://partnershiponai.org/resources/
  • Responsible AI Practices – [https://ai.google/principles/

Data Ethics & Privacy

  • GDPR Compliance – gdpr.eu
  • Data Privacy Best Practices – datatilsynet.no

Prompt Engineering

  • OpenAI Prompt Engineering Guide – platform.openai.com/docs
  • Anthropic Prompt Library – docs.anthropic.com
  • Prompt Engineering Tutorial – learnprompting.org

Demo & Presentation Skills

  • How to Demo Your Project – Y Combinator guide
  • Pitch Deck Templates – pitch.com
  • Video Recording Tools – Loom, OBS Studio
  • Screen Recording – QuickTime, Windows Game Bar, ShareX

Datasets & APIs

General:

  • Data.gov – US government open data
  • Kaggle Datasets – kaggle.com/datasets
  • Google Dataset Search – datasetsearch.research.google.com
  • AWS Open Data – registry.opendata.aws

Social Good:

  • UN Data – data.un.org
  • World Bank – data.worldbank.org
  • Our World in Data – ourworldindata.org

 

Stay Connected

 

Pre-Submission Checklist

Ethics & Responsible AI:

- ✅ Identified potential biases?

- ✅ Explained what AI doesn't do?

- ✅ Kept humans in control of key decisions?

- ✅ Disclosed data sources and limitations?

- ✅ Tested with diverse scenarios?

 

Technical:

- ✅ All code tested and working?

- ✅ Demo accessible to judges?

- ✅ Video uploaded and link tested?

- ✅ All tools and data disclosed?

- ✅ README or documentation complete?

 

Submission:

- ✅ All required fields completed?

- ✅ Qualifier approval code entered?

- ✅ Character limits respected?

- ✅ Team members all listed?

- ✅ Submitted before deadline?

 

Need more help? Join Discord or email aihackathon@usaii.org

 

Good luck building! 🚀