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Learning outcomes
Tier 1 - ML in Weather & Climate
- Identify key concepts in Machine Learning, numerical weather and climate prediction.
- Describe the main topics in numerical weather and climate prediction, and the relevance of Machine Learning in each.
- Understand the added value and limitations of Machine Learning in weather and climate.
Tier 2 - Concepts of Machine Learning
- Learn and apply the most important ML techniques relevant to ML in weather and climate applications.
- Select and design ML workflows and apply them to simplified real-world problems.
Tier 3 - Practical ML applications in Weather & Climate
- Discover the state of the art ML research throughout the key applications of numerical weather and climate predictions.
- Gain practical experience in the use of code and data in real research projects.
- Develop a real case study in at least one of the main topics of numerical weather and climate prediction, by applying the practical application of ML workflows.
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Programme of the MOOC
Tier 1 - ML in Weather & Climate
This first tier is an introduction to Machine Learning in weather and climate. It is addressed to anyone interested in the topic, from research to operations. Only a basic knowledge of weather and climate science, statistics and informatics is assumed of learners.
Tier 2 - Concepts of Machine Learning
The second tier is an engaging and more practical dive into the concepts of Machine Learning. It is particularly well suited for technical data users from academia or industry across different sectors.
Tier 3 - Practical ML applications in Weather & Climate
The third tier demonstrates practical Machine Learning applications in weather and climate. Addressing the same audience as Tier 2, it also gives learners the opportunity to apply Machine Learning to real world problems.