Modeling and Predicting Climate Anomalies
Master climate data modeling. Predict extreme events and evaluate policies using machine learning techniques.
Master climate data modeling. Predict extreme events and evaluate policies using machine learning techniques.
This comprehensive specialization combines climate policy analysis, statistical modeling, and machine learning applications in environmental science. Students learn to evaluate global climate policies, analyze climate data using Python, and develop predictive models for extreme weather events. The program provides hands-on experience with real-world datasets, advanced analytical techniques, and practical applications in climate science. Whether you're a data scientist, climate researcher, or policy professional, you'll gain essential skills in climate data interpretation, modeling, and prediction.
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What you'll learn
Analyze and evaluate global climate policies and their impacts, master statistical analysis techniques for climate data using Python, develop machine learning models to predict extreme climate events, visualize and interpret climate anomalies using advanced tools, implement supervised and unsupervised learning algorithms, apply dimensionality reduction techniques to complex datasets, work with real-world climate data through API integration.
Skills you'll gain
This course includes:
44 Hours PreRecorded video
3 course assessments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 3 courses in this program
Global Climate Change Policies and Analysis
Course 1 · 14 Hours to complete · 4 modules
Modeling Climate Anomalies with Statistical Analysis
Course 2 · 7 Hours to complete · 3 modules
Predicting Extreme Climate Behavior with Machine Learning
Course 3 · 23 Hours to complete · 5 modules
Fee Structure
Payment options
Financial Aid
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