MSc Data Science and Environmental Intelligence

• 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

  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.

  MAR538
  Marine Environmental Monitoring

  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.

  COMP5000
  Software Development and Databases

  This 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.

  MATH517
  Big Data Visualisation and Analytics 20 credits

  Sophisticated techniques are needed to visualize and analyse increasing quantities of Big Data. This module introduces the modern data science techniques and professional software to handle large complex datasets, as well as experience of writing professionally documented code and data analysis reports. Data analysis pipelines, including data cleansing, are used to produce data visualizations and statistical analysis.

  100% Coursework

  MATH518
  Applied Data Modelling and Artificial Intelligence

  This module provides an understanding of modelling and analytics techniques for Data Science. It covers modern data modelling techniques for making strategic decisions in a broad range of Business related practical situations. Students get a hands-on introduction to: Bayesian inference, machine learning, and artificial intelligence. It provides additional practice in making professional presentations.

  Optional modules

  GEES520
  MSc Dissertation

  The 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 Dissertation

  The 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.

• 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