Key features
- Hands-on, experiential learning.
- Industry-focused content that prepares students for working with emerging cutting edge technologies.
- Teaching led by academics actively driving change.
- A sustainability-based education that empowers students to make a difference.
- A specific focus on environmental intelligence – sensing, monitoring and management through the use of automation, AI and big data.
- By combining core skills in computing and data analysis with knowledge of a range of innovative environmental sensors and the ability to analyse big data you will develop the interdisciplinary skills and knowledge to take a leading role in environmental analytics and in providing practical solutions to 21st century global challenges.
- After completing the taught programme and dissertation, you will have the opportunity to consolidate your learning by undertaking an optional 6–12-month industry placement in the terrestrial or marine environmental sectors.
- A diverse and respectful place in which to work and study is fundamental to everything we do. Find out more about
equality, diversity and inclusion in the School of Geography, Earth and Environmental Science .
Course details
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Year 1
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The MSc Data Science and Environmental Intelligence programme provides a diverse curriculum to teach you the skills required to become proficient in data collection, management, and analysis to meet the current and future demands of the data economy with a particular focus on environmental systems and data.During the first two semesters of the one-year taught programme you will gain essential computing skills such as software development and coding, modelling and machine learning, and advanced statistical data handling with a focus on big data. Alongside developing your technical expertise, you will learn how environmental data are collected and analysed, and how such data are essential for sustainable development. In particular, our new facilities in terrestrial and marine sensors, and ground-breaking work on marine autonomous vehicles, will open your eyes to the future of environmental sensing technology.In the final semester, you will complete an independent dissertation project with a focus on either a terrestrial or marine issue. Throughout your studies you will be supported in gaining the research and professional skills to help you succeed in the programme and to launch a successful career.
Core modules
APIE502
Placement PreparationThis module is aimed at students who may want to undertake an optional industrial placement upon completion of the taught programme. It is designed to assist students in their search for a placement, and preparation for the placement itself.
GEES531
Environmental Observations and Quality Assurance 20 creditsThis module introduces the fundamental concepts of ‘the analytical approach’ to working with environmental problems, including student-lead case studies that allowing them to learn and apply the principles of good practice for observational data collection, quality control and traceability. Research study skills sessions are included, leading to the planning of a research dissertation.
100% Coursework
GEES535
Terrestrial Environmental Sensors and Big DataTerrestrial sensor networks are revolutionising the design of urban environments, as well as informing land and catchment management. This module builds upon the semester 1 by providing students with the opportunity to solve real-world questions relating to sustainability challenges using expanded datasets from automated sensors and environmental observations used in current earth and environmental science research.
MAR538
Marine Environmental MonitoringMonitoring of the marine environment provides data that underpins research, exploitation, management and policy development. Students will learn about the practicalities of reliable marine data collection using autonomous platforms and sensors, be introduced to secondary data sources from across the subject area, and develop associated skills in spatial and time-series data analysis techniques and interpretation.
MATH501
Modelling and Analytics for Data ScienceThis module gives students an understanding of modelling and analytics techniques for Data Science. It supplies modern data modelling tool boxes for making strategic decisions in a broad range of Business related practical situations. It offers a hands-on introduction to Bayesian inference and machine learning. It provides additional practice in making professional presentations.
MATH513
Big Data and Social Network VisualizationSophisticated analytics techniques are needed to visualize today's increasing quantities of Big Data. Up-to-date R tools including dplyr for data manipulation, ggplot2 for visualization, and knitr/LaTeX for document presentation are studied. These are applied to database interrogation, social network visualization and sentiment analysis. The module provides considerable experience of writing professionally documented R code using RStudio.
COMP5000
Software Development and DatabasesThis module will provide knowledge and skills in software development and database design. It will cover computational problem solving, abstraction and problem decomposition. The module will enable students to identify appropriate system requirements related to the relational database model.
Optional modules
GEES520
MSc DissertationThe student will complete an independent research project that they have designed in semester 1 as part of their research skills development. The record of the research will communicate the project aims, research problem, methodology, data analysis, interpretation, discussion/synthesis and conclusions in the format specified and to a professional standard.
MAR524
MSc DissertationThe student will complete a research project that they have designed in the semester 1 research skills module. The project can be submitted in the format of a journal paper or dissertation. The write-up will communicate the project aims, methodology, data analysis, interpretation, synthesis and conclusions.
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Optional placement year following completion of the taught programme
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Core modules
APIE503
Industry PlacementThis module enables students to take a 6-12 month placement linked to their programme. Assessment is based on Progress Reports, Regional Tutor evaluation, Employer evaluation and self-evaluation via reflective report (or portfolio).
Every postgraduate taught course has a detailed programme specification document describing the programme aims, the programme structure, the teaching and learning methods, the learning outcomes and the rules of assessment.
The following programme specification represents the latest programme structure and may be subject to change:
Entry requirements
Fees, costs and funding
Student | 2024-2025 | 2025-2026 |
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Home | £11,000 | £11,350 |
International | £19,800 | £20,400 |
Part time (Home) | £610 | £630 |
Additional costs
Postgraduate scholarships for international students
Tuition fees for optional placement years
How to apply
When to apply
Before you apply
- evidence of qualifications (degree certificates or transcripts), with translations if not in English, to show that you meet, or expect to meet the entry requirements
- evidence of English language proficiency, if English is not your first language
- a personal statement of approximately 250-400 words about the reasons for your interest in the course and outlining the nature of previous and current related experience. You can write this into the online application form, or include it as a separate document
- your curriculum vitae or résumé, including details of relevant professional/voluntary experience, professional registration/s and visa status for overseas workers
- proof of sponsorship, if applicable.
Disability Inclusion Services
International students
Submitting an application
What happens after I apply?
Telephone: +44 1752 585858
Email: admissions@plymouth.ac.uk
Admissions policy
Learn more about the programme, its relevancy to real world issues and the career opportunities available.
Specialist facilities
Dr Cho Kwong Charlie Lam
Academic staff
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Dr Cho Kwong Charlie Lam
Lecturer in Environmental Science
Programme leader
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Dr Simon Ussher
Associate Professor of Marine and Analytical Chemistry
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Professor Alex Nimmo Smith
Professor of Marine Science and Technology
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Dr Marco Palomino
Visiting Associate Professor
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Professor Tony Morris
Professor in Geophysics and Geodynamics
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Professor Paul Russell
Professor of Coastal Dynamics