University of Colorado Boulder
Modeling and Predicting Climate Anomalies Specialization
University of Colorado Boulder

Modeling and Predicting Climate Anomalies Specialization

Master Climate Data Analysis and Modeling. Learn to analyze climate data, evaluate global policies, and apply machine learning to predict extreme climate events.

Osita Onyejekwe

Instructor: Osita Onyejekwe

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Get in-depth knowledge of a subject
Intermediate level

Recommended experience

1 month at 10 hours a week
Flexible schedule
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Share your expertise with employers
Get in-depth knowledge of a subject
Intermediate level

Recommended experience

1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers

What you'll learn

  • Analyze global climate policies and their impact

  • Apply statistical analysis techniques in Python to model and interpret climate data using tools like SciPy and NumPy

  • Develop and implement machine learning models to predict extreme climate events and analyze climate anomalies using real-world datasets

Overview

What’s included

Shareable certificate

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Taught in English
9 practice exercises

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from University of Colorado Boulder

Specialization - 3 course series

What you'll learn

  • Identify climate goals and policies, such as the Kyoto Protocol and the Paris Agreement. 

  • Describe the impacts of climate change.

  • Evaluate the technological, economic, and policy challenges associated climate change mitigation strategies.

Skills you'll gain

Climate Change Mitigation, Environmental Policy, Forecasting, Policy Analysis, Emerging Technologies, Sustainable Technologies, Public Policies, Environmental Science, Governance, Energy and Utilities, Pollution Prevention, Climate Change Adaptation, Environment, and International Relations

What you'll learn

  • Visualize and interpret climate anomalies using statistical analysis.

  • Use APIs to import climate data from government portals.

  • Visualize data in Python with matplotlib. 

Skills you'll gain

Matplotlib, Application Programming Interface (API), Data Manipulation, Pandas (Python Package), Data Analysis, Data Visualization, Statistical Analysis, Time Series Analysis and Forecasting, NumPy, Regression Analysis, Data Collection, Statistical Modeling, and Data Integration

What you'll learn

  • Analyze and differentiate between various machine learning algorithms, including unsupervised and supervised methods

  • Apply dimensionality reduction techniques, such as Principal Component Analysis (PCA) and Singular Value Decomposition (SVD), to complex datasets

  • Implement supervised learning algorithms using Python, and evaluate their performance through practical exercises and real-world case studies.

  • Develop and apply effective clustering methods to analyze and segment data

Skills you'll gain

Supervised Learning, Unsupervised Learning, Regression Analysis, Dimensionality Reduction, Machine Learning, Artificial Neural Networks, Data Processing, Applied Machine Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Feature Engineering, Data Science, Classification And Regression Tree (CART), Statistical Analysis, and Machine Learning Algorithms

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Instructor

Osita Onyejekwe
University of Colorado Boulder
5 Courses3,277 learners

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