Domains using pandas
Predict Tomorrow's Wind Speed for Flight Planning
Build a weather model that helps pilots make go/no-go decisions
Download historical airport weather data (METAR observations) and build a simple machine learning model that predicts next-day wind speed. Learn how pilots use weather forecasts for flight planning and go/no-go decisions.
Start Project → AI/MLPredict Clear-Air Turbulence from Weather Data
Build a classifier that warns pilots about invisible rough air
Build a machine learning classifier that predicts turbulence severity (none/light/moderate/severe) from atmospheric variables using real NOAA pilot reports (PIREPs) and reanalysis data. Tackle one of aviation's most challenging weather hazards.
Start Project →Track Nearby Aircraft with ADS-B and Visualize Patterns
Tap into live aircraft data and discover hidden flight patterns
Use the OpenSky Network API to collect real aircraft position data, plot flight paths on a map, compute basic statistics, and use k-means clustering to discover flight patterns. Your first data science project with real-time aviation data.
Start Project → Some AI/MLClassify Aircraft Types from ADS-B Trajectories
Identify what's flying overhead from how it flies
Extract flight trajectory features from OpenSky Network ADS-B data — climb rate, speed profile, turn radius, acceleration patterns — and train a classifier to identify aircraft types. Learn feature engineering on spatiotemporal data.
Start Project →Calculate and Compare Carbon Footprints of Different Flights
Turn flight data into climate insight with Python
Use public flight data to calculate CO2 emissions per passenger-kilometer for different aircraft types and routes. Build a simple regression model that predicts emissions from distance and aircraft size.
Start Project → Some AI/MLPredict Flight Fuel Burn from Route and Aircraft Data
Build an ML model that estimates fuel consumption before takeoff
Use publicly available flight data from BTS or Eurocontrol to build a regression model predicting fuel consumption from distance, aircraft type, payload, and weather. A real-world ML problem with direct sustainability applications.
Start Project → AI/MLPredict Pilot Fatigue Risk from Flight Schedule Data
Model the invisible threat to flight safety with ML
Model cumulative fatigue using the SAFTE/FAST framework, then train an ML model on schedule features to predict fatigue risk scores. Tackle one of aviation safety's most challenging human factors problems.
Start Project →