Data Analysis: Tools for Environmental Scientists

About this programme

Credit ChatGPT4, picture generated by Ida Rahu using the prompt “Data Analysis Tools for Environmental Scientists. R and Python. Data pipelines - from raw data to visualizations (bar charts, scatter plots, and maps related to climate change, pollution, and biodiversity) and modeling” In the emerging era of “big data”, it is more essential than ever for natural and social scientists to have high data literacy and the ability to rapidly interpret and interrogate data for answers to targeted questions. Join this course and you will get an introduction, and basic skills in the modern, open-source programming languages R and Python, both of which are among the most-used programming languages in the world. Through targeted workshops and hands-on laboratory exercises, you will explore essential tools and libraries while learning practical data analysis workflows – from data input and cleaning to exploration, visualization and model-building. The course covers descriptive statistics, hypothesis testing and predictive modeling. You will apply these data analysis techniques using real-world datasets relevant for environmental challenges including climate change, pollution, and biodiversity loss. You need to have access to your own laptop in order to participate in the course's computer labs. This is a course in applied mathematics and scientific programming. The best way to learn math and the best way to learn programming is to actually do it! Following this philosophy, course meetings will feature short lectures where key concepts are introduced, followed directly by workshop