1. Overview

The Fourth Industrial Revolution (4IR) has brought about new technologies that produce a huge amount of data, making it more important in many research areas. This shift towards data is clear in both natural and social sciences. As more fields depend on data, the need for practical data science skills is rapidly growing

In response, Hack4dev is launching Data Science (DS) Hackathons to provide participants with hands-on experience in fast-paced environments grounded in real-world research projects.

2. Objectives

Our Data Science Hackathons have the following main objectives:

• Equip participants with the skills necessary to solve and communicate real-world research problems in machine learning.
• Accelerate research in social science by using hackathons to investigate novel tools like ChatGPT and educational models like the flipped classroom.
• Enhance research outcomes in data science across different fields through the research conducted by participants while solving real-world problems.

3. Methodology

The implementation of data science hackathons will follow a structured framework, as outlined on our Vision page, divided into two key stages: Trainers Hackathons (TH) and Regional Hackathons (RH). This approach is designed to build capacity among senior researchers and regional organizing teams, equipping them to run successful hackathons within their own institutions.

3.1 Trainers Hackathons (TH)

This stage educates regional organising teams on conducting hackathons, empowering them to host their events in their regions with minimal Hack4dev team support. Trainers gain firsthand experience in both technical and logistical facets, guided by the experienced Hack4dev members.

3.2 Regional Hackathons (RH)

Here, regional teams organise a hackathon at their institutions, where the broader impact is realised, and data is generated through conducted surveys.

4. Scope

The aim is to recruit and train diverse, skilled teams to organise hackathons at their local institutions. Each organising team aims to train approximately 30 regional hackathon participants.

• TH Scope: During a 3-4 day workshop, train several teams on orchestrating Hack4dev Data Science hackathons, encompassing both technical and logistical components.  
• RH Scope: Organizing teams, supported by Hack4dev, will conduct all regional hackathons within a designated 3-month period, following a structured 3-day program to ensure consistency in data gathering and analysis

5. Calls for Participation

Explore our annual calls to join and contribute to impactful Data Science hackathons, whether as a trainer or participant.

6. Resources

Explore our helpful resources, featuring complete data science research projects with detailed Jupyter notebooks, draft hackathon programs, and sample surveys.