MSc Environmental Data Science and Analytics

As global discussions are increasingly focused on the environment and sustainability, the need to understand and interpret both built and natural environmental data is more crucial than ever. Governments, organisations, and industries across the world are seeking individuals who can leverage data to make informed, sustainable decisions. Our Environmental Data Science and Analytics MSc is designed to give you a fuller understanding of data and what appropriate interpretation and insight generation means in various environmental contexts. Throughout, you'll develop a broad understanding of environmental issues and how data driven analysis can help address these. You’ll build the skills needed to analyse, understand, interpret and visualise complex environmental data; generating insights that address real-world environmental challenges. You’ll apply techniques from data science including environmental modelling, machine learning, visualisation and data curation to environmental data, with a focus on analysis through programming. Here at Leeds, you’ll have the opportunity to learn from leading researchers in the field, with input from the School of Geography, the School of Earth and Environment, and the School of Computer Science. By the end of the course, you’ll be equipped with the specialist knowledge and skills that are sought after across multiple industries, especially those dealing with large scale environmental data to address the needs of society. Why study at Leeds: Our globally-renowned research from the School of Geography, School of Earth and Environment and the Leeds Institute for Data Analytics, the national institute for data science and artificial intelligence feeds into the course, shaping your learning with the latest thinking in environmental data science and analytics. Advance your skills and knowledge in areas such as environmental policies, programming for data science, machine learning, AI, satellite technology and interpreting large hyperdimensional data. Tailor the course to suit your career aspirations with a selection of optional modules in areas like web-based GIS, GIS and environment and digital image processing for environmental remote sensing. Conduct your own project work which will enable you to develop transferable skills as a researcher, investigating a real-world issue that explores and develops your interests. Access specialist facilities which will complement your learning including laboratories and an excellent GIS computer cluster with industry-standard software. Experience expert theoretical and practical teaching delivered by a programme team of academics who are actively engaged in ground-breaking research in the School of Geography and the School of Earth and Environment. Put theory into practice with exciting fieldwork opportunities, allowing you to develop the understanding and skills in data acquisition and deployment of sensors to collect environmental data. Related coursesUrban Data Science and Analytics MSc This Masters degree is a great fit for students interested in urban processes and using data-driven solutions to provide insight for future planning and policies. Like our Environmental Data Science and Analytics MSc, you’ll build key skills in data wrangling, machine learning, data analysis, visualisation and creative coding – but with a specialised focus surrounding an urban context. See course page Air Quality Solutions with Data Science MSc Take a data science approach to a broad range of air quality-related topics, including emissions, monitoring, modelling, pollution exposure, health impacts and policy and economic appraisal. From Clean Air Zones to managing indoor sources of air pollutants, you’ll use research-led pollution-monitoring techniques to critically evaluate the impact of these interventions. See course page.

A bachelor degree with a 2:1 (hons) in a relevant subject Those with a background in geography, environmental science, natural sciences, or related discipline, who can also demonstrate good quantitative and/or computing skills are particularly encouraged to apply Alternatively, those with a background in engineering, computer science, or related discipline, with demonstratable academic, volunteer, or work-based experience are also encouraged to apply Applicants should also possess a keen interest in harnessing data science to understand the natural environment and address environmental issues Applicants with any of the following will be considered on a case-by-case basis:Several years of professional experience in a relevant field where applicants do not meet….