MSc Data Science and Artificial Intelligence (Earth and Environmental Analytics) / Course details

From climate change to environmental degradation, tackling global challenges depends on understanding complex data. Our MSc Data Science and Artificial Intelligence (Earth and Environmental Analytics pathway) uses data science methodologies and generative AI models to analyse environmental challenges, assess risk and generate insights that support a more sustainable future.

Throughout your studies, you will develop valuable data science skills while exploring environmental challenges such as climate change, biodiversity and conservation, natural hazards, and environment and health.

You will build skills in data analysis, project design, computational methods, managing agentic AI, data stewardship, and more.

You will receive rigorous training in statistics and machine learning, databases, data environments and applying data science to solve problems. Your focus will largely be on the data techniques and uses that are most relevant to environmental intelligence and environmental management, with optional course units exploring themes such as pollution control, environmental monitoring and modelling, geocomputing and subsurface geoscience.

You will be taught by an interdisciplinary team through lectures, computer-based practicals, e-learning, meetings with industry partners, workshops, group work and individual research.

We welcome applicants from a range of STEM, business and humanities backgrounds, allowing us to create a diverse cohort and enrich discussions around the uses and potential of data.

By the end of your studies, you will have developed a highly valued skillset, enhancing your employability across countless sectors such as policy, business, research and more.

This course will:

• Provide an opportunity for graduates from a broad range of disciplines to develop data science skills.
• Prepare you to understand and respond to the complex interactions between the environment, climate, natural ecosystems, human social and economic systems, and health.
• Train you to ask important research questions, evaluate the quality of available evidence, select appropriate methods and use analytical skills to visualise, interpret and provide strategic advice and insight.
• Enable you to develop into an agile, skilled data scientist adept at working in a variety of settings, able to meet the challenges and rewards of interdisciplinary teamwork.
• Prepare you for new and exciting training across cutting edge data science and environmental science technologies to integrate multiple complex data sources and create tools that enable informed decision making for future environmental systems.

Interdisciplinary approach

Gain a comprehensive understanding of data analytics through studying varied aspects and applications of data science from Statistics, Demography, Social Networks, Data Science, Economics, Politics, Criminology, Health, Sociology, and other fields.

Hands-on

Make theory come alive with hands on experience analysing real-world data using a variety of statistical software such as R, Python, Excel and more.

This course is taught by an interdisciplinary team using a variety of delivery methods:

• lectures;
• computer based practicals;
• e-learning;
• meetings with industry partners;
• workshops;
• group work;
• individual research.

Course units are assessed in a variety of ways, including:

• exams;
• essays;
• reports;
• online tests;
• video and in person presentations;
• presenting code files;
• group work;
• practical skills assessments.