Data Science for Climate Change

Big data and the algorithms used in data science, together with the corresponding process and its technology tools, have important implications for addressing climate change. From machine learning algorithms to data visualization, data science methods are used to investigate and better understand climate change and its various effects on land, sea, food, etc.Data science is a powerful approach which is capable of helping practitioners, and policy-makers understand the uncertainties and ambiguities inherent in data, to identify interventions, strategies, and solutions that realize the benefits for humanity and the environment, and to evaluate the multiple– and sometimes conflicting–goals of decision-makers. In this MOOC course, we introduce methods pertaining to the growing field of data science and apply them to issues relevant to climate change. Topics Data science Analytics as a process Data-driven decisions Climate change Applications of data science in climate change Course content Understand data science Learn about the sources of big data Understand the basics of climate change, its impacts and sustainable development goals Get to know data-driven decisions and how they are made Highlight some climate change challenges that are directly or indirectly related to data science Apply data science knowledge and skills to make climate change related decisions Learn how others have used data science in association with addressing climate change problems You will learnBy the end of the course, you will be able to: obtain and analyze datasets; make data-driven decisions; identify and address climate change challenges using data science Who is the course for?This course is designed for those who want to improve their analytics and data-driven decision-making skills, with an emphasis on utilizing such skills for addressing climate change challenges. The course will also be useful for practitioners and policy-makers as they can benefit from understanding the uncertainties and ambiguities inherent in data and using it to identify interventions, strategies, and solutions that realize benefits for humanity and the environment.