Introduction

Welcome to the DTP Full Stack Developer Hackathon! This is your space to learn, build, and connect with Rwanda’s digital innovators.

📍 Project Objective

Learners will work as individuals to design, develop, and present an AI-powered solution that addresses a real-world business problem. The solution should demonstrate the full cycle of AI development, from problem definition to model deployment and monitoring.

 

🧩 Project Component
 ● Problem Identification and Data Exploration: Define a clear business problem and explore relevant datasets.
 ● Model Development: Build a machine learning model using Python, applying algorithms learned in the program.
● AI Integration: Integrate the model into a practical application, such as a chatbot, dashboard, or predictive analytics tool.
● Responsible AI Practices: Demonstrate ethical considerations, bias management, and explainability in model development.
● Problem-Solving Documentation: Record the entire problem-solving process, from defining the issue to monitoring the solution.
● Communication Strategy: Document communication workflows, updates, and team decision-making processes.
 ● Team Presentation: Present the developed AI solution, share results, demonstrate application functionality, and reflect on challenges and learning points. 
✅ Project Objectives
Project Title:

 AI-Powered Business Solution 

Project Description:

 Develop and deploy an AI-powered solution that addresses a real-world business challenge. The solution must include a functional AI model, integration into an application, and demonstration of responsible AI principles.

 

 📤 Key Deliverables:

 ● Problem Statement and Data Summary 

● Model Development Files

 ● Application Integration (Chatbot, Dashboard, etc.) 

● Responsible AI Practices Report

 ● Problem-Solving Log

 ● Team Communication Records

 ● Final Presentation Slide Deck

  • Programming Languages

    • Python (most popular)

    • R (for statistical modeling)

  • Data Science & ML Libraries

    • NumPy, Pandas (data analysis)

    • Scikit-learn (machine learning)

    • TensorFlow, Keras, PyTorch (deep learning)

Inspiration

- [Devpost Student Hackathons](Link)