Data Science (MSc)

About the Course

In today’s world, almost every interaction we have is through digital technology—whether it’s on a computer, smartphone, camera, or smartcard. These interactions create data, which can be analysed to improve decision-making, systems, and research.

Thanks to advancements in technology, computational power, and machine intelligence, a new field has emerged: Data Science.

Instead of just focusing on business metrics or financial markets, we’re now analyzing data about people and the world they live in. As Jake Porway, Executive Director of DataKind, explains: “A data scientist is a rare combination of a computer scientist, who can build software to manage data from various sources, and a statistician, who knows how to extract valuable insights from that data. They prototype new ideas and ask the most important questions about what the data can reveal.” This course is designed for people like this.

Built on the expertise of the Mathematics and Computer Science departments, this program blends new technologies, groundbreaking research, and fresh scientific perspectives to prepare you to shape the future of society in meaningful ways.

Note: Some international partners offer this course as part of a two-year program.

Curriculum Overview

Core Modules

The MSc in Data Science aims to equip postgraduate students with core skills in:

• Applied Computer Science
• Data Analytics
• Machine Learning Algorithms
• High-performance Computing
• Theoretical Computer Science
• Numerical Methods
• Big Data
• Internet-of-Things

Assessments

The ethos within the School is to foster enthusiasm for Computer Science and so assessment is largely through project work, giving you the opportunity to explore the subject area and focus on those specific topics that capture your interest. The project entails research and innovation as well as practical industrial applications of the ideas developed during the programme of study.

The dissertation gives you the opportunity to use the skills gained throughout the PG taught provision. Students are expected to specialise in a specific area of research in order to create something new, or to scientifically investigate research questions and independently solve problems in an innovative way. During this practice you should reflect the scientific process and be self-reflective, critical and clear in its explanation of its hypothesis and synthesis of ideas.

Each individual dissertation is worth 60 credits and this is expected to be a student led investigation into a relevant area of Computer Science. A “pool” of topics is available that reflects the research interests of the staff within the department, however, a student can propose their own topic which is then considered by the PG coordinator. Ultimately the research topic needs to be agreed with and approved by the PG coordinator. Students are assigned to a specialist tutor that guides them through the research process. We strongly encourage our students to produce publishable research work, where possible, and thus provide an opportunity to jointly publish their research work with members of the team. Workload allocation is in accordance with the agreed Common Dissertation Policy for allocation and supervision.

Entry Requirements

A minimum of a second class honours degree in a relevant discipline (eg Data Science, Computer Science, Computing, Science, or engineering-based) awarded by a UK university, or an equivalent higher education qualification.

International Entry Requirements

Possess a degree from an overseas institution that is judged by the Registrar or Nominee to be equivalent to a second class honours degree from a UK University.

For students whose first language is not English there is a language requirement of IELTS 6.5 overall with 6 minimum of all components. In addition to this, we also accept a wide range of International Qualifications, for more information please visit our English Language Requirements page.

For additional information about country specific entry requirements visit the your country pages. 

*Part time study is not available for Non-UK applicants

Teaching and Research

The course is delivered by a passionate and dedicated team that takes pride in both its high teaching standards—recognized independently—and its vibrant research community. In the most recent Research Excellence Framework (REF) Exercise, 100% of the School's research was rated as internationally excellent or recognized. Our staff specialize in a wide range of fields, including Robotics, Bio-inspired Systems, Deep Learning Networks, Machine Intelligence, Virtual and Augmented Reality, Cognitive Mobile Networks, Cyber Security, Mathematical Modelling, and more.

Our state-of-the-art Robotics Laboratory in our Science Building, features cutting-edge technologies such as industry-standard software (e.g., Matlab/Simulink, Labview, Visual Studio, 3D Studio Max), as well as Virtual Reality and Augmented Reality interfaces (e.g., Oculus Rift). The lab is equipped with a variety of advanced robots (e.g., Kilobot swarm robots, Aldebaran Nao, i-Sobot, Moway Robotic Buggies), embedded systems for physical computing (e.g., Arduino, Xilinx Zynq), communication modules, wearable and biomedical sensors, motion capture systems, and even UAVs and drones. This is a place where technology and innovation come to life!

Home Fees

Tuition fees for Home students for 2026/27 are £10,000

Tuition fees for Home students for 2027/28 are £10,500

International Tuition Fees

Tuition fees for Non-UK International students for 2026/27 are £17,500

Tuition fees for Non-UK International students for 2027/28 are £17,750

Funding your studies

If you're a UK national, or have settled status in the UK, you may be eligible to apply for a Postgraduate Loan to help with course fees and living costs. Liverpool hope University also offers a number of scholarships to help fund your Postgraduate Studies. Learn more about paying for your studies.

If you are an international student, visit our international scholarships pages.

Careers

The demand for Data Scientists is growing rapidly, with year-on-year increases of 13% to 23%. Currently, 46% of industries report having difficulty recruiting skilled staff. As this is a relatively new field, very few potential Data Scientists possess the unique combination of programming, statistics, and specific subject knowledge required.