Tips for Excelling in a Data Science Hackathon
This guide offers essential strategies for succeeding in data science hackathons, focusing on solution demonstration, data science techniques application, and efficient presentation. It includes a concise checklist, a step-by-step approach to problem-solving, and an Idea Library with innovative tools like ChatGPT and Whisper for project development.

Here is a downloadable Canva Document of the guide: [Data Science Hackathon Guide]
Solution Checklist:
- Solve the challenge: How does your solution address the challenge?
- Demo your application: Use Gradio, Power App, or a full-stack web app(best to start with a template).
- Apply data science techniques: Employ regression/characteristic model or generative AI.
- Efficient presentation: Use PowerPoint or Google Slides. Practice your presentation.
Problem-Solving Approach:
- Review each challenge and associated dataset.
- Analyse the dataset to identify data that can bolster your solution.
- Draft user stories for your solution.
- Define the Minimum Viable Product (MVP).
- Finalise the features and establish the data flow.
- Develop the model and application.
- Deploy and conduct testing.
- Prepare and deliver the presentation.
Idea Library with Innovative Tools:
- Co-pilot Type
- Text Summarisation: ChatGPT API
- Audio to Text: Whisper(local model)
- Chat with your document: LangChain
- Demonstration Platform: Colab + Gradio
- Background knowledge: Deeplearning.ai
- Dashboard Type