Overview
- Degree awarded
- Master of Science (MSc)
- Duration
- 1 year
- Entry requirements
-
High 2:1 honours degree (or overseas equivalent)
We require that all applicants have a strong background in Computer Science reflected, for example, in solid programming and software development skills. We typically expect a First or strong Upper Second class honours degree, or the overseas equivalent, in Computer Science, or in a joint degree with at least 50% Computer Science content. We may consider a lower proportion where a student has performed consistently strongly in their computer science modules. Applicants with extensive Computer Science industrial experience and an honours degree in Computer Science, or its overseas equivalent, may also be considered for admission.
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.
Please see our application and selection page for more detailed information.
- 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).
- Study within a uniquely interdisciplinary programme that brings together expertise from across Manchester’s facilities, giving you both strong foundations within the field, and the opportunity to collaborate across disciplines to tackle local and global challenges.
- Gain hands-on experience analysing real-life data using a variety of programming languages for data analysis, including R, Python, and SQL among others.
- Develop highly desirable professional skills to pursue a career in diverse areas such as 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).
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
- pg-soss@manchester.ac.uk
- Website
- https://www.socialsciences.manchester.ac.uk/social-statistics/
- School/Faculty overview
-
See: School Subjects
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)
We require that all applicants have a strong background in Computer Science reflected, for example, in solid programming and software development skills. We typically expect a First or strong Upper Second class honours degree, or the overseas equivalent, in Computer Science, or in a joint degree with at least 50% Computer Science content. We may consider a lower proportion where a student has performed consistently strongly in their computer science modules. Applicants with extensive Computer Science industrial experience and an honours degree in Computer Science, or its overseas equivalent, may also be considered for admission.
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.
Please see our application and selection page for more detailed information.
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
- Pearson Test of English (PTE) score of 76 overall and no component score below 70
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.
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 (Computer Science Data Informatics) course prepares you for a successful career in this high-demand field.
You will 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.
If you’re looking to specialise in the technical and computational side of data science, our course is well-suited to meet your needs. You will focus on the data techniques and uses that are most relevant to computer science.
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.
- 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.
Special features
Interdisciplinary approach
Gain a comprehensive understanding of data analytics through studying varied aspects and applications of data science from Demography (Population Studies), Social Networks, Urban Planning, Climatology, Business Analytics, Finance Economics, Politics, Criminology, Health, 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 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;
- Applying Data Science.
Optional course units range from statistical foundations to data engineering and cognitive robotics, preparing you with a varied but strong foundation in data and computer science.
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 8500-word extended research project. Your project will mirror a real-world data science investigation, including replication code and an accompanying overview video for stakeholders. Your dissertation must be within the area of one of the course units you have chosen.
Your extended research project 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.
| Title | Code | Credit rating | Mandatory/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 |
| Data Engineering Concepts | COMP63301 | 15 | Optional |
| Data Engineering Technologies | COMP63502 | 15 | Optional |
| Reinforcement Learning | COMP64202 | 15 | Optional |
| Cognitive Robotics and Computer Vision | COMP64301 | 15 | Optional |
| Displaying 10 of 11 course units | |||
| Display all course units | |||
Disability support
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 across sectors:
- banking and financial services;
- charities and research organisations;
- The Civil Service;
- the IT and tech sector;
- business management;
- high performance sports analysis;
- large retail chains;
- the pharmaceutical industry.
Many students also choose to continue specialising for a career in research and universities through a PhD at Manchester, or another leading institution, preparing for a career in research or academia.
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.