What you will learn:

Unlocking the Copernicus Climate Data Store (up to 20 hours of learning)
• Science and data science
• Provide a checklist of learner prerequisites and hardware needs
• Overview of climate science
• Data driven discovery in climate science and climate change: techniques and data types
• Needs analysis: defining the research question through examples
• Interviews with creators of climate datasets, including EO and climate modelling
• Further reading on statistics and climate change

General introduction to C3S datasets and sectoral applications
• Explanations of observations, reanalysis, seasonal forecasts and climate projections
• Using the catalogue – worked examples
• Data: physical significances, uncertainties, missing data, data quality
• Examples of sectoral applications

Examples from the Climate Data Store
• Examples of climate indicators for sectoral applications, include at least two climate and at least two seasonal forecast
• Introduction to the toolbox, APIs and reanalysis
• Worked exercises to download, analyse and visualise datasets – observations, reanalysis, seasonal forecasts and climate projections
• Introduction to using Python APIs

What will you achieve?
By the end of the course, you’ll be able to…

Explain the characteristics and identify sources of big data
Explore applications of data in environmental science for business
Understand the skills necessary to be a data scientist
Discuss the importance of open data and participate in citizen science