Weather Wizard: How ML and Bayesian Stats Can Forecast Storms Better
The 16-session plan
Research and compile a list of at least 5 ML techniques used in weather forecasting and their applications in predicting severe storms.
Create a timeline and outline data sources for collecting historical weather data, focusing on variables like temperature, humidity, and pressure.
Implement a Python script to preprocess the collected weather data, ensuring it is clean and structured for analysis.
Study Bayesian statistics concepts and create a visual representation of how prior distributions can influence storm prediction outcomes.
Frequently asked questions
Who is this project a great fit for?+
BlueRobins projects are designed for curious students in Grades 3-12 who want to build. No prior experience is needed — mentors start wherever your child is and grow the challenge as they grow.
What does a typical session look like?+
Your child meets 1-on-1 with their mentor every week over Google Meet. Programs run 16 sessions of 45 minutes each. Sessions are hands-on from minute one — building, designing, coding, writing, experimenting — with the mentor coaching live, asking great questions, and unlocking the next step.
What will my child build by the end?+
A finished project they're proud of and can show the world. Across 16 sessions, your child turns an ambitious idea into a working app, prototype, research write-up, portfolio, or published artifact. Every student finishes with a completion certificate signed by their mentor.
Why a free trial first?+
So your child can meet their mentor, get a feel for the project, and leave the call excited. The trial is a complimentary 1-on-1 free trial session — no credit card needed. After the trial, you decide if it's the right fit. Most families know within the first 15 minutes.