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• Year 1

• 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 Preparation

  This 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 credits

  This 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 Data 20 credits

  Terrestrial 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.

  60% Coursework

  40% Practicals

  MAR538
  Marine Environmental Monitoring 20 credits

  Monitoring 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.

  60% Coursework

  40% Practicals

  COMP5000
  Software Development and Databases 20 credits

  The critical first part of a data science project is extracting and cleaning the data (dealing with missing values, for example.) In this module you will be taught how to use a programming language to do common data science tasks, such as data cleaning, and how to build a Graphical User Interface to a program. You will also learn the design of relational databases, and the extraction of data from a database using SQL.

  100% Coursework

  MATH517
  Big Data Visualisation and Analytics 20 credits

  There is an ever increasing amount of Big Data available. You will learn state-of-the-art techniques for extracting valuable information and insights from Big Data. We'll teach you professional software to clean, visualize and analyse complicated datasets. We'll also provide you with experience of professional reporting your Big Data analyses.

  100% Coursework

  MATH518
  Applied Data Modelling and Artificial Intelligence 20 credits

  We'll teach you state-of-the-art modelling and analytics techniques for Data Science, so that you can provide informed strategic advice in a broad range of business and related situations. You'll meet techniques to extract knowledge from data and to update that knowledge when new observations become available. We'll also discuss popular Machine Learning algorithms for making classification decisions.

  100% Coursework

  Optional modules

  GEES520
  MSc Dissertation 60 credits

  This is your chance to take on independent, postgraduate-level research project. You get to choose a topic that excites you, work with expert advisors, and dive deep into cutting-edge methods and analysis. You'll challenge ideas, explore new perspectives, and develop real expertise. In the end, you’ll present your findings in a dissertation and showcase your research - proving just how far you’ve come.

  100% Coursework

  PROJ522
  MSc Dissertation 60 credits

  The student will complete an independent research project that they have designed. The project can be submitted in a journal paper format, a dissertation or another written format as appropriate to the discipline. The write-up will include project aims, research problem to be addressed, methodology, data analysis, interpretation, discussion/synthesis, conclusions, supported by Figures and Tables, as appropriate.

  100% Coursework

• Optional placement year following completion of the taught programme

• Core modules

  APIE503
  Industry Placement

  This 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).

MSc Data Science and Environmental Intelligence programme specification_7575