About the challenge

ReverieHacks is the biggest and most unique virtual hackathon for students to showcase their projects to the world and earn prizes along the way. Students can join in teams of 1-3 in one of several tracks to design projects from their dreams and compete for various awards.

About our tracks

Our hackathon features six distinct tracks, each designed to showcase and develop a variety of skills among high school students. These tracks are:

  • Ideathon: A track where teams collaborate to brainstorm, refine, and develop innovative ideas into comprehensive project plans. Participants will have the opportunity to explore creative solutions, receive feedback, and turn their concepts into viable projects.
  • ML Prompt Engineering: A track where teams design and optimize AI workflows to achieve the best possible results for specific purposes. Participants will focus on creating efficient and effective workflows using LLM models like ChatGPT and Gemini, employing structured queries to ensure the most optimized output based on the given input.
  • Software Development: A track centered around traditional hackathon experiences where teams design software solutions to unique problem.
  • Datathon: A track where teams use machine learning and data science techniques to analyze datasets and identify patterns to solve specific problems. Participants will not only be finding trends, but also analyzing them to gain insights into a possible solution.
  • Embedded Systems: A track meant for those interested in computer and electrical systems. Within this track, teams will be making use of ecad software for developing hardware solutions like pcbs for specific purposes.
  • App Development: A track meant for those enthusiastic about creating applications for mobile devices. Unlike software development where teams may present projects about any program, this track is specially for mobile applications.

Each track offers a unique challenge, allowing participants to highlight and enhance their specific talents.

For more information you can check out our page.

Requirements

Ideathon

Building your idea: In this track, you will be developing a possible solution to a problem you've identified. The first step for developing your solution would be figuring out basic context like who is affected, what is the problem, why is it there. Then will be the part of actually designing a proper solution that could work and properly address the problem and figuring out relevant project details like Value Proposition, Customer Segments, Channels, Customer Relationships, Revenue Streams, Key Resources, Key Activities, and Cost Structure. Find more here.

Submitting your Project: For the ideathon track, you are required to submit 2 different files:

  • Pitch Presentation: Record a small video (no longer than 5 mins) which is your pitch that covers the purpose of your project as well as key details.
  • Project Plan: A pdf document that covers all details regarding the project like purpose, technical details, mockups, logistics as well as your future plans for the project. It would be a good idea to include extra details in this document and focus only on key details in the pitch presentation.

 

ML prompt engineering

Building your project: For the ML prompt engineering track, students interested in the application of LLMs will be designing workflows that help obtain an output for specific purposes through human input and structured queries via ML models like GPT, Gemini.

Submitting your project: For the ML prompt engineering track, you are required to submit 4 different files:

  • ML workflow: Upload a png of the flowchart version of your ML workflow that depicts where human inputs is necessary, what queries are used with LLMs, which LLM model is used and what each action does.
  • Samples: Prepare a video/document that shows the use of workflow for sample test cases as compared to using a single prompt approach with the same test cases.
  • Documentation: Include a detailed documentation that explains the reasoning behind each node in the Ai workflow, how it works and any other necessary data.

 

Software development

Building your project: The building process for the software development track is fairly simple and your goal is to create a software solution. It is important that you do it on github along with relevant licensing to help protect your project. It is also vital that you follow our guidelines which can be found here.

Submitting your project: For the software development track, you are required to submit 4 different files:

  • Code repository: Upload the complete project code to a version control platform such as GitHub, GitLab, or Bitbucket. Ensure the repository is accessible and includes necessary instructions.
  • Demo video: Create a video that demonstrates the functionality, features, and user interface of the software. The video should highlight key aspects and use cases.
  • Documentation: Provide a detailed Project documentation that includes information like purpose, target audience and main features, but also technical things like installation guides, user manuals, references and any configuration or setup instructions.

 

Datathon

Building your project: The building process for the datathon track starts with identifying the problem you want to solve and finding relevant datasets. Datasets can be easily found on kaggle.com. The next step would be writing the code for exploring and processing the dataset, and then training a model around it. Finally, the team will work to interpret the results and derive meaningful conclusions from it, and prepare necessary documentation.

Submitting your project: For the datathon track, you are required to submit 4 different files:

  • Code repository: Upload the complete project code to a version control platform such as GitHub, GitLab, or Bitbucket. Ensure the repository is accessible and includes necessary instructions to run/replicate.
  • Dataset: Within your Github README file, you have to include a link to the dataset used in your project.
  • Report: Prepare a document that explains your results and analysis, the methodology employed, reasoning behind certain crucial decisions and your evaluation of the model training process.
  • Demo video: Create a video that best demonstrates your trained model or your results.

 

Embedded systems

Building your project: The building process for embedded systems starts with finding a problem you want to solve. You can find find problems that you go through daily or inconviences that you face on a regular basis. Then comes the designing process. Starting with picking out the components you need, you should start designing a circuit. Once you are happy with the circuit you have designed and have created a schematic that works, you can begin converting it into a PCB.  You should be constantly using Design Rules Check (DRC) to ensure that your design doesn't violate any issues. 

Submitting your project: For the embedded systems track, you are required to submit 4 different files:

  • File directory: Upload the complete project to an online storage solution such as GitHub or google drive. Ensure the directory is accessible and includes necessary instructions. This should contain schematics of your circuit as well as any other design.
  • Firmware: If your circuit uses any MCU, then you must upload the relevant code in your file directory. It is highly reccomended to include a flowchart of your algorithm to make the code easy to understand. 
  • Demo video: Create a video that demonstrates the designed product. The video should highlight key aspects and use cases.
  • Tech report: Prepare a document that gives tech specs and explains your product in detail.

 

App Dev

Building your idea: In the app development track, you will be building programming an app around the problem. However, it is also vital to consider other important factors like Ui/Ux while designing your app. Find more here.

Submitting your Project: For the app dev track, you are required to submit 3 different files:

  • Code repository: Upload the complete project code to a version control platform such as GitHub, GitLab, or Bitbucket. Ensure the repository is accessible and includes necessary instructions.
  • Demo video: Create a demo video of the app, showing off its features as well as other features like the UI.
  • Project documentation: Provide a detailed Project documentation that includes information like purpose, target audience and main features, but also technical things like installation guides, user manuals, references and any configuration or setup instructions for using the app.

Hackathon Sponsors

Prizes

$600+ in prizes
+ other prizes
App Development 1st Place
$75 in cash
1 winner

App Development 2nd Place Prize
$25 in cash
1 winner

Datathon 1st Place Prize
$75 in cash
1 winner

Datathon 2nd Place Prize
$25 in cash
1 winner

Embedded Systems 1st Place Prize
$75 in cash
1 winner

Embedded Systems 2nd Place Prize
$25 in cash
1 winner

Ideathon 1st Place Prize
$75 in cash
1 winner

Ideathon 2nd Place Prize
$25 in cash
1 winner

ML/AI Prompt Engineering 1st Place Prize
$75 in cash
1 winner

ML/AI Prompt Engineering 2nd Place Prize
$25 in cash
1 winner

Software Development 1st Place Prize
$75 in cash
1 winner

Software Development 2nd Place Prize
$25 in cash
1 winner

Wolfram|One 1 Year Subscription (worth $1,660)
30 winners

Wolfram|One 1 Year Subscription (worth $1,660 each) provided to 30 members of top-performing teams that make projects using the provided free trial of Wolfram|One tools.

MakeX Sponsor Prize
3 winners

Winning Ideathon projects that utilize the MakeX AI app will receive a MakeX 1 year subscription (worth $120 each).

Devpost Achievements

Submitting to this hackathon could earn you:

Judges

Tanmay Kejriwal

Tanmay Kejriwal
MakeX Founder

Chirag Agarwal

Chirag Agarwal
Amazon Senior Engineer

Saurabh Kakkar

Saurabh Kakkar
Financial Professional

Jawad Ali

Jawad Ali
Keycense Software Engineer

Jeet Mehta

Jeet Mehta
Netflix Software Developer

Gokul Balaguruswamy Naidu

Gokul Balaguruswamy Naidu
Capital One Software Engineer

Pratik Sheth

Pratik Sheth
Google Technical Lead

Niyati Prajapati

Niyati Prajapati
Google Gen AI/ML Lead

Haoyuan He

Haoyuan He
Netflix Software Engineer

Pallavi Moghe

Pallavi Moghe
Musa Co-Founder

Ashwini Joshi

Ashwini Joshi
Warner Bros Machine Learning Engineer

Ram Joshi

Ram Joshi
Staff Engineer | The Climate Corporation

Mahendra Chenniah

Mahendra Chenniah
Healthcare Software Architect | CVS

Arjun Mullick

Arjun Mullick
Engineering Manager | Meta

Omkar Ashok Bhalekar

Omkar Ashok Bhalekar
Senior Network Engineer | Tesla

Mantas Eringis

Mantas Eringis
Software Engineer | Blockdaemon

Ashutosh Tripathi

Ashutosh Tripathi
Senior Manager | CLARA Analytics

Prajwalkumar Bhatkar

Prajwalkumar Bhatkar
Senior Lead Software Engineer | Capital One

Judging Criteria

  • Innovation
  • Problem Solving
  • Sustainability/Scalability
  • User Experience & Design
  • Bonus: Exceptionality

Questions? Email the hackathon manager

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