MSc Data Science (Earth and Environmental Analytics) / Course details
Year of entry: 2024
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The range of pathways reflects the interdisciplinary nature of the course and we welcome applications from students with backgrounds in a range of disciplines, including:
- Business and Management;
- Health Science;
- Social Sciences;
- Computer Science;
We provide training in core data science skills, embedded in a disciplinary context provided by the pathway, you will develop:
- computational skills;
- data analytical skills;
- data stewardship skills and knowledge;
- project design skills.
This innovative MSc in Data Science course is an opportunity for graduates from a broad range of disciplines to develop data science skills. Our goal is to help you develop into an agile, skilled data scientist, adept at working in a variety of settings and be able to meet the challenges and reap the rewards of interdisciplinary teamwork.
There is growing evidence across academia, policy makers and industry that `Environmental Intelligence (EI)' is an emerging research area of strategic global importance. Its primary aim is to understand and respond to the complex interactions between the environment, climate, natural ecosystems, human social and economic systems, and health.
Key areas of concern include:
- Climate Change (e.g., resilient cities, clean power, smart transport options, sustainable production).
- Biodiversity and Conservation (e.g., habitat protection and restoration, pollution control, realizing natural capital), Natural Hazards (e.g., predicting and forecasting, early warning systems, resilient infrastructure).
- Environment and Health (e.g., air quality, water and sanitisation, social and environmental inequalities).
Mapped to The University of Manchester's research strengths, the aim of this pathway is to 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.
Course unit details
Through a set of core units, you will develop a set of key data science skills.
The core units are:
- Machine Learning and Statistics (both semesters);
- Understanding Databases;
- Understanding Data and their Environment;
- Applying Data Science
Course unit list
The course unit details given below are subject to change, and are the latest example of the curriculum available on this course of study.
|Statistics and Machine Learning 1: Statistical Foundations||DATA70121||15||Mandatory|
|Applying Data Science||DATA70202||15||Mandatory|
|Understanding Data and their Environment||DATA71011||15||Mandatory|
|Extended Research Project||DATA72000||60||Mandatory|
|Measuring and Predicting 2||EART60071||15||Optional|
|Computational Subsurface Geoscience||EART60152||15||Optional|
|Key Interpretation Skills||EART60381||15||Optional|
|Earth and Environmental Data Science||EART60702||15||Optional|
|Environmental Monitoring and Modelling||EART62012||15||Optional|
|Displaying 10 of 18 course units|
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