MSc Data Science (Earth and Environmental Analytics)

Year of entry: 2026

Overview

Degree awarded
Master of Science (MSc)
Duration
1 year
Entry requirements
  • high 2:1 honours degree (or overseas equivalent)
  • See application and selection tab.

    In your application, you should demonstrate aptitude, knowledge and/or interest in three areas:

    • data analytics and/or statistics;
    • computational subjects; and
    • pathway specific requirements.

    These can be demonstrated by course units taken at undergraduate level and high school level, or professional experience.

    For this Pathway we would expect applicants to evidence an interest and/or experience in topics related to environmental analysis. Examples are:

    • Working experience in environment-themed topics (e.g. environment, climate, natural ecosystems, human social and economic systems, and health)
    • Experience in working in data science, GIS or environmental based data analysis

    Evidence of training in environment-themed methods or topics

    Full entry requirements

    How to apply
    Apply online

    Course options

    Full-time Part-time Full-time distance learning Part-time distance learning
    MSc Y N N N

    Course overview

    • Study a master’s in Data Science at a university ranked top 10 in the UK for maths, statistics and computer science (Times Higher Education World University Rankings by Subject, 2025).
    • Join a uniquely interdisciplinary department that develops and applies data-driven insights to the fields of property, policy, town planning and beyond.
    • Gain hands-on experience analysing real-life data using a variety of statistics software such as R, Python, Excel among others.
    • Apply data driven insights to current environmental challenges such as Climate Change, Biodiversity and Conservation, Natural Hazards, and Environment and Health.
    • Develop highly desirable professional skills that are sought after across a range of sectors, including policy, business, research and more.
    • Graduate from one of the UK’s most targeted universities by top employers (High Fliers, The Graduate Market Report 2024).
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    Explore the new MSc in Data Science

    Open days

    The University holds regular open days, where you will have the opportunity to find out more about our facilities and courses.   

    On this day, you will find out more about the School, our resources, and meet academic and admissions staff who will be able to answer any questions you have.   

    For more information, see open days and visits .

    Fees

    For entry in the academic year beginning September 2026, the tuition fees are as follows:

    • MSc (full-time)
      UK students (per annum): £17,300
      International, including EU, students (per annum): £35,200

    Further information for EU students can be found on our dedicated EU page.

    Policy on additional costs

    All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).

    Scholarships/sponsorships

    For information on available scholarships please visit: Master’s Fees and Funding

    Contact details

    School/Faculty
    School of Social Sciences
    Contact name
    School of Social Sciences Admissions Office
    Telephone
    +44 (0) 161 306 5500
    Email
    Website
    https://www.socialsciences.manchester.ac.uk/social-statistics/
    School/Faculty overview

    Courses in related subject areas

    Use the links below to view lists of courses in related subject areas.

    Entry requirements

    Academic entry qualification overview

  • high 2:1 honours degree (or overseas equivalent)
  • See application and selection tab.

    In your application, you should demonstrate aptitude, knowledge and/or interest in three areas:

    • data analytics and/or statistics;
    • computational subjects; and
    • pathway specific requirements.

    These can be demonstrated by course units taken at undergraduate level and high school level, or professional experience.

    For this Pathway we would expect applicants to evidence an interest and/or experience in topics related to environmental analysis. Examples are:

    • Working experience in environment-themed topics (e.g. environment, climate, natural ecosystems, human social and economic systems, and health)
    • Experience in working in data science, GIS or environmental based data analysis

    Evidence of training in environment-themed methods or topics

    English language

    Applicants whose first language is not English should meet the following language requirements:

    • IELTS Academic test score of 7 overall with no component score below 6.5
    • TOEFL IBT 100 with no score below 22 in each section. TOEFL code for Manchester is 0757
    Pre-Sessional English Courses

    We will consider applicants who do not meet these scores but you may be required to complete a pre-sessional English language course at the University of Manchester prior to the start of the course.

    To be considered for a pre-sessional English language course for this programme we require the following minimum IELTS (Academic) scores:

    6 Week Pre-Sessional Course : IELTS 6.5 overall with 6.0 in each sub-skill  

    10 Week Pre-sessional Course : IELTS 6.0 overall with 6.0 in three sub-skills, and 5.5 in no more than one sub-skill  

    If you have not yet completed your current academic study and are interested in studying a pre-sessional course, you must hold an IELTS for UKVI (Academic) test certificate to ensure that you are eligible for a separate visa for the English language course.

    English language test validity

    Some English Language test results are only valid for two years. Your English Language test report must be valid on the start date of the course.

    Applicants from Majority English-speaking countries

    If you are a national of a   majority English-speaking country   (or have studied for a full bachelor's degree or higher from one of these countries) you may be exempt from submitting further evidence of English language proficiency.

    Other international entry requirements

    We accept a range of qualifications from across the globe. To help international students, the university provides specific information for many individual countries. Please see our  country-specific information page   for guidance on the academic and English language qualifications which may be accepted from your country.

    Application and selection

    How to apply

    Staged admissions

    In your application, you should demonstrate aptitude, knowledge and/or interest in three areas:

    • data analytics and/orstatistics;
    • computationalsubjects;
    • pathway specific requirements.

    These can be demonstrated by course units taken at undergraduate level and high school level, or professional experience.

    Staged Admissions

    As there is a high demand for our courses, we operate a staged admissions process with selection deadlines throughout the year. Due to the competition for places and high quality of applications that we receive, we give preference to students from high ranking institutions and with grades above our minimum entry requirements.

    Please ensure you submit all supporting documentation with your application to avoid a delay in processing.

    Applications for 2026 entry:

    Stage 1: Application received by 7th December 2025 ; Application update by 20th February 2026

    Stage 2: Application received by 1st March 2026 ; Application update by 1st May 2026

    Stage 3: Application received by 3rd May 2026 ; Application update by 19th June 2026

    Stage 4: Application received by 5th July 2026 ; Application update by 31st July 2026

    Whilst we aim to give you a decision on your application by the deadline date, in some instances due to the competition for places and the volume of applications received, it may be necessary to roll your application forward to the next deadline date.

    Applications received after our final selection deadline will be considered at our discretion if places are still available.

    Please note: All places are subject to availability and if you apply at one of the later stages, some courses may already be reaching capacity or be closed to further applications. We, therefore, recommend that you apply early in the cycle to avoid disappointment.

    Course details

    Course description

    The inexorable rise of the digital world, driven by rapid AI development, has made data scientists more in demand right now than ever before. The advances of analysing big data span beyond the digital and technology industry and are increasingly recognised in the worlds of sport, medicine, space exploration and more. Our MSc Data Science (Earth and Environmental Analytics) course prepares you for a career in this high-demand field.

    You’ll develop invaluable abilities in key area’s such as:

    • data analysis;
    • project design;
    • computational methods;
    • data stewardship.

    See a full list of mandatory and optional course units below.

    This course focuses on the data techniques and uses that are most relevant to environmental management, with optional course units exploring themes such as pollution control and subsurface geoscience.

    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. Previous students have gone on to roles such as data scientists, civil servants, consultants, researchers, entrepreneurs, and in AI.

    Aims

    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.

    Special features

    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.

    Teaching and learning

    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.

    Coursework and assessment

    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.

    Course unit details

    A master’s degree is formed of 180 credits.

    120 of these credits are made up by a mix of mandatory and optional course units, worth 15 credits each. You will need to select eight of these course units, with 60 credits taken each semester.

    The core units are:

    • Machine Learning and Statistics (both semesters);
    • Understanding Databases;
    • Understanding Data and their Environment;
    • Applications in Data Science.

    Optional course units range from statistical foundations to environmental based data analysis and GIS, preparing you with a varied but strong foundation in data and environmental analytics.

    The availability of individual optional course units may be subject to change. Information that is sent to you in August about registration onto the course will clearly state the course units that are available in the academic year ahead.

    The remaining 60 credits are awarded through a compulsory research component in the form of a 12,000-to-15,000-word dissertation. Your dissertation must be within the area of one of the course units you have chosen.

    Your dissertation research is supported by weekly research methodology lectures designed to improve your academic, research and writing skills.

    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.

    TitleCodeCredit ratingMandatory/optional
    Statistics and Machine Learning 1: Statistical Foundations DATA70121 15 Mandatory
    Statistics & Machine Learning 2: AI, Complex Data, Computationally Intensive Statistics DATA70132 15 Mandatory
    Understanding Databases DATA70141 15 Mandatory
    Applying Data Science DATA70202 15 Mandatory
    Understanding Data and their Environment DATA71011 15 Mandatory
    Extended Research Project DATA72000 60 Mandatory
    Privacy, Confidentiality and Disclosure Control DATA70402 15 Optional
    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
    Pollutant Mobility and Transformation EART62022 15 Optional
    Pollution Management in Practice 2 EART63012 15 Optional
    Environmental Remote Sensing GEOG60941 15 Optional
    GIS and Environmental Applications GEOG60951 15 Optional
    Understanding GIS GEOG71551 15 Optional
    Neighbourhood Planning Project PLAN60812 15 Optional
    Displaying 10 of 18 course units

    Disability support

    Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: dass@manchester.ac.uk

    Careers

    Career opportunities

    The University of Manchester is one of the most targeted universities by the UK’s top graduate employers (High Fliers, The Graduate Market Report 2024).

    This innovative MSc in Data Science provides you with the data skills required for a range of careers within:

    • banking and financial services;
    • The Civil Service;
    • the IT and tech sector;
    • high performance sports analysis;
    • large retail chains;
    • the pharmaceutical industry.

    The University has its own dedicated, award-winning Careers Service where you can benefit from tailored careers support, practice interviews, CV and application support, job listings for Manchester students, and much more. Better yet, you will have access to our Careers Service both during your course and for two years after you graduate, so we know you’re on the right path.