What Does MVP Stand For? It’s Not What You Think.
October 7, 2024
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Master Climate Data Analysis and Modeling. Learn to analyze climate data, evaluate global policies, and apply machine learning to predict extreme climate events.
Instructor: Osita Onyejekwe
Included with
Recommended experience
Intermediate level
Familiarity with Python programming is recommended.
Recommended experience
Intermediate level
Familiarity with Python programming is recommended.
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
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November 2024
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In this specialization, you’ll gain a comprehensive foundation in climate change policies, statistical modeling, and machine learning, all applied to the context of global climate challenges. You will learn how to critically evaluate climate policies, analyze climate data using Python, and leverage machine learning to predict extreme weather behaviors. With a focus on real-world applications you'll develop practical skills to interpret and model climate data to address one of the most pressing issues of our time.
Whether you’re a data scientist, climate researcher, or policy advocate, this specialization provides a hands-on approach to mastering the tools and concepts that can help mitigate and adapt to the impacts of climate change.
This specialization can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.
Applied Learning Project
Throughout the specialization, you'll work on real-world projects that involve accessing climate data through API calls, analyzing and visualizing trends, and applying machine learning models. By the end of the specialization, you'll practice selecting a region of interest, collecting and cleaning climate data, and using advanced analytical techniques to model and predict climate anomalies.
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.
Visualize and interpret climate anomalies using statistical analysis.
Use APIs to import climate data from government portals.
Visualize data in Python with matplotlib.
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
CU Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
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The specialization requires about three to six hours of work a week for twelve weeks to complete.
Learners should have some experience working with Python programming.
Yes, it's recommended that learners new to data mining take the three courses in the specialization in sequence.
No, but the Modeling Climate Anomalies specialization is part of CU Boulder's Master's of Science in Data Science program. Learners enrolled in this program will earn credit toward the degree by completing this specialization.
By the end of the specialization, you will be able to analyze climate policies, collect and model climate data, and apply machine learning techniques to predict extreme climate events.
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.
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