Overview
Data is everywhere, shaping the way we make decisions, solve problems, and understand the world. Statistics provide the foundation for interpreting complex data, drawing accurate conclusions, and building robust models. When combined with data science, we can handle larger datasets and gain clear and reliable insights. Leading to more informed and effective solutions.
You’ll graduate from this Master’s degree with advanced knowledge in mathematics, statistics and data science. You’ll gain a unique skillset that’s attractive to employers across a wide range of industries.
This programme offers great flexibility, allowing you to design a degree to match your interests and career goals. You can personalise your studies by choosing from a broad range of modules and you’ll benefit from our diverse research expertise.
You can explore topics such as:
- data visualisation
- machine learning
- extreme value theory
- image analysis
- sports modelling
To personalise your degree, you can choose between two dissertation modules:
- Industrial dissertation: Work with a business to solve a real-world data science problem using your new skills.
- Individual research project: Study and research a topic in your own area of interest.
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Important information
We’ve highlighted important information about your course. Please take note of any deadlines.
Your course and study experience – disclaimers and terms and conditions
Please rest assured we make all reasonable efforts to provide you with the programmes, services and facilities described. However, it may be necessary to make changes due to significant disruption, for example in response to Covid-19.
View our Academic experience page, which gives information about your Newcastle University study experience for the academic year 2024-25.
See our terms and conditions and student complaints information, which gives details of circumstances that may lead to changes to programmes, modules or University services.
Qualifications explained
Find out about the different qualification options for this course.
MSc – Master of Science
An MSc is a taught Master’s degree. It usually involves the study of a science-related subject.
You’ll usually study an MSc full-time over 12 months.
A Master of Science is typically awarded for the successful completion of 100 credits of taught modules and an 80-credit dissertation or research project.
Find out about different types of postgraduate qualifications.
What you’ll learn
Semester 1
In Semester 1, you’ll build a solid foundation in data science, statistics, machine learning and image informatics.
Semester 2
You’ll begin to customise your degree in Semester 2. You’ll choose five optional modules to suit your interests and aspirations. These can include topics such as:
- time series modelling
- design of experiments
- financial modelling
- survival analysis
- decision modelling for health data
Semester 3
In Semester 3, you’ll choose one of these dissertation modules:
- industrial dissertation
- individual research project
The industrial dissertation is perfect if you want to focus on strengthening your employability. You’ll work with a business to solve a real-world data problem.
During the individual research project, you’ll create your own project which focuses on your own interests and career aspirations.
Modules
You will study modules on this course. A module is a unit of a course with its own approved aims and outcomes and assessment methods.
Course content changes
Module information is intended to provide an example of what you will study.
Our teaching is informed by research. Course content changes periodically to reflect developments in the discipline, the requirements of external bodies and partners, and student feedback.
Full details of the modules on offer will be published through the Programme Regulations and Specifications ahead of each academic year. This usually happens in May.
To find out more please see our terms and conditions.
Optional modules availability
Some courses have optional modules. Student demand for optional modules may affect availability.
Advanced Data Science with Statistics MSc modules
Compulsory modules
- Computing Foundations of Data Science (10 credits)
- Image Informatics (10 credits)
- Machine Learning with Project (10 credits)
- Graduate Foundations of Statistics and Data Science (30 credits)
- Statistical Foundations of Machine Learning with Advanced Topics (10 credits)
You must choose one of the following modules:
- Dissertation in Statistical Data Science (60 credits)
- Industrial Dissertation in Statistics and Data Science (60 credits)
Optional modules
You must choose 50 credits from the following list of optional modules:
- Clinical Trials with Advanced Topics (10 credits)
- Decision Modelling for Health Data Science with Advanced Topics (10 credits)
- Advanced Topics in Medical Statistics and Health Data Science (10 credits)
- Experimental Design with Advanced Topics (10 credits)
- Extreme Value Theory with Advanced Topics (10 credits)
- Sports Modelling with Advanced Topics (10 credits)
- Survival Analysis with Advanced Topics (10 credits)
- Time Series with Advanced Topics (10 credits)
- Stochastic Financial Modelling with Advanced Topics (10 credits)
- Advanced Topics in Statistics and Data Science (10 credits)
How you’ll learn
You’ll be taught using a range of methods, including:
- lectures
- seminars
- practical labs
- workshop sessions
- group work
Depending on your modules, you’ll be assessed through a combination of:
- Case study
- Dissertation
- Oral presentation
- Report
- Written examination
- Written exercise
Numbas learning software
You’ll have access to a specialist learning software called Numbas. Developed at Newcastle University, it’s now used by mathematicians and statisticians worldwide.
This innovative software allows you to work on interactive code worksheets, so you can test and refine your skills throughout your course.
Specialist software and tool support
You’ll have support from our award-winning Digital Learning Team, who can assist you with the specialised software and tools you need for the programme.
Your teaching and learning is also supported by Canvas. Canvas is a Virtual Learning Environment. You’ll use Canvas to submit your assignments and access your:
- module handbooks
- course materials
- groups
- course announcements and notifications
- written feedback
Throughout your studies, you’ll have access to support from:
- peers
- academics
- personal tutors
- our University Student Services Team
- student representatives
You’ll also be assigned an academic member of staff. They will be your personal tutor throughout your time with us. They can help with academic and personal issues.
The Advanced Data Science with Statistics MSc is delivered jointly by the:
The degree is delivered by experts working at the frontier of a wide range of statistical and computer science areas.
You’ll work alongside academics from the following research groups:
- Statistics: World-class research in modern statistics and data science.
- Astrostatistics: Cutting-edge research being carried out at the interface of physics and statistics. They’re using modern data science techniques to help understand the universe.
- Scalable Computing: Internationally renowned for tackling research challenges in high performance systems, data science, machine learning and data visualisation.
- Biostatistics: Over 30 statisticians working in developing and applying innovative methods in clinical trials and observational studies.
We’re also home to the UK’s National Innovation Centre for Data (NICD). This gives you unique opportunities to collaborate with industry partners across multiple sectors.
Many of our staff are fellows of the Alan Turing Institute. They play a key role in shaping the way data science is researched and taught in the UK and around the world.
Your development
Professional skills
You’ll enhance your professional skills by writing reports and delivering presentations to both experts and non-experts. Working on projects will improve your teamwork and communication skills. If you choose the industrial dissertation, you’ll also gain valuable experience working with a business to meet deadlines.
Research skills
You’ll build your research skills by:
- sourcing and analysing datasets
- assessing data to answer research questions
- critically evaluating your own work and others
You’ll also reflect on your research process to identify areas for improvement.
Practical skills
You’ll develop advanced practical skills for data science, including programming, data manipulation and effective visualisation.
You’ll learn to:
- source, clean, and process data
- apply statistical techniques
- evaluate model performance
You’ll also draw predictions while creating reports that integrate your analyses and insights.
Your future
Your career
This Advanced Data Science with Statistics MSc can provide a pathway to various careers across a broad range of industries. Job roles might include:
- Data Scientist
- Data Analyst
- Data Engineer
- Sports Analyst
- Medical Statistician
- Business Analyst
- Quantitative Analyst
Previous students from our data science courses have gone on to work at companies such as:
- LEGO
- Bank of England
- AkzoNobel
- Department of Workplace and Pensions (DWP)
Further study
This degree provides a route into PhD level study in a wide range of fields, depending on your choice of optional modules.
As a Data Science graduate, you can focus on advanced research in data science and statistical methods, with applications in areas such as:
- machine learning and artificial intelligence
- data ethics and fairness
- experimental design
- extreme value theory
- sports modelling
- survival analysis
- time series analysis
- health data science and clinical trials
- decision modelling in healthcare
- natural language processing
Links with industry
You’ll benefit from our connections with industry leaders, gaining access to valuable networking opportunities, internships, and insights into real-world applications of data science.
Our academics have connections with:
- National Health Service (NHS)
- United Nations
- World Health Organisation (WHO)
- Department for Transport and National Highways
- Met Office
- Smartodds
Our Careers Service
Our award-winning Careers Service is one of the largest and best in the country, and we have strong links with employers. We provide an extensive range of opportunities to all students through our ncl+ initiative.
Quality and ranking
- 42% of our research is classified as 4* world-leading research – Research Excellence Framework 2021
- 65% increase in research power since 2014 – Research Excellence Framework 2021
- Global Top 130 University – QS World University Rankings 2025
- Global Top 170 University – Times Higher Education World University Rankings 2024
- Top 200 for Statistics and Operational Research – QS World University Rankings by Subject 2024
- Top 25 in the UK and Top 100 in the world for sustainable development – Times Higher Education Impact Rankings 2024
Recognition of professional qualifications outside of the UK
From 1 January 2021 there is an update to the way professional qualifications are recognised by countries outside of the UK
Facilities
Urban Sciences Building
The School of Computing is based in the £58 million Urban Sciences Building (USB), a flagship development located on the £350 million Newcastle Helix regeneration site in the heart of Newcastle. It brings together:
- academia
- the public sector
- communities
- business and industry
Postgraduate student facilities
As a Master’s student, you’ll have access to specialist teaching spaces and facilities in the USB. These are only available to postgraduate students.
Wellbeing and inclusivity are at the heart of our School. The USB has several wellbeing spaces for students, including:
- The Retreat: A sensory space with relaxing stimuli to distract from busy student life.
- Wellbeing room: Designed for relaxation and quiet time. Here you can take a moment to breathe and unwind. It can also be used by students with special medical requirements.
- Prayer room: For all faiths and none, this space can be used for prayer or quiet reflection.
Entry requirements
The entrance requirements below apply to 2025 entry.
Academic entry requirements
A 2:1 BSc honours degree, or international equivalent, in mathematical sciences or another quantitative degree with a formal mathematical component. Examples include, but are not limited to, computer sciences, economics, engineering and similar disciplines.
Applicants from a non-standard background and individuals with strong relevant work experience are encouraged to apply and will be considered on an individual basis.
