Projects / Local Chapter Challenge

Improving Extreme Weather Forecasts Using AI

Challenge Started!


Omdena Featured image

This Omdena Local Chapter Challenge runs for 6 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world.

You will work on solving a local problem, initiated by the Omdena Silicon Valley, USA Chapter.

The problem

In this 4-week project, the team will model data to predict the arithmetic mean of the maximum and minimum temperature over the next 14 days for each location and start date for longer-term weather forecasting to help communities adapt to extreme weather events caused by climate change.

Various Machine Learning methods can be used to make these predictions, such as Random Forests, XGBoost, and Convolutional Neural Networks (CNNs). The team will explore several choices.

Data can be augmented with meteorological data such as temperature, wind speed, and vapor pressure from National Oceanic and Atmospheric Administration (NOAA).  

One of the key challenges will be to choose a subset of appropriate features that impact a weather forecast’s predictions to be used in model training.

The goals

The goals of this challenge are: 

  • Data Collection and Exploratory Data Analysis
  • Preprocessing 
  • Feature Extraction
  • Model(s) Development and Training
  • Evaluate the best Model

Why join? The uniqueness of Omdena Local Chapter Challenges

Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level.

A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.

Read more on how Omdena´s Local Chapters work

First Omdena Local Chapter Challenge?

Beginner-friendly, but also welcomes experts

Education-focused

Open-source

Duration: 4 to 8 weeks



Your Benefits

Address a significant real-world problem with your skills

Build your project portfolio

Access paid projects (as an Omdena Top Talent)

Get hired at top organizations



Requirements

Good English

Suitable for AI/ Data Science beginners but also more senior collaborators

Learning mindset



This challenge is hosted with our friends at



Application Form

Related Projects

media card
Building Climate and Credit Risk Scoring for African SMEs With AI
media card
CanopyWatch - Enhancing Deforestation Monitoring and Conservation in the Congo Basin using Machine Learning
media card
ESG Insight: Transforming Risk Assessment with Data and Machine Learning

Become an Omdena Collaborator

media card
Visit the Omdena Collaborator Dashboard Learn More