Data Science & Artificial Intelligence MSc

Volume. Velocity. Variety. Veracity. Compiling meaningful conclusions out of unstructured data poses challenges never faced before. Master the theories, algorithms and techniques that untangle large and complex data sets on a Masters degree awarded initial accreditation by BCS, The Chartered Institute IT (subject to re-approval).

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Overview

Course length:	12 months full-time 2-3 years part-time
Start dates:	January 2025 September 2025 January 2026
Location:	Edge Hill University
Subject(s):	Computer Science
Faculty:	Arts and Sciences
Department:	Computer Science

A student talks to a tutor during a lecture.

What revelations hide in social media, online reviews, mobile applications or Internet of Things (IoT) sensor data? Our MSc Data Science & Artificial intelligence unlocks the theories, skills and tools you need to uncover hidden patterns, correlations and trends.

As a recent graduate of a STEM discipline or IT industry career changer, you’ll become a data specialist on this course.

Data scientists and analysts work in a changing and evolving technology landscape. You need imagination and creativity to come up with novel ways to answer questions. We’ll teach you to assess new and advanced solutions then adapt them as you process, analyse and make sense of big and complex data.

Study visualisation, modelling, and the foundations of artificial intelligence and machine learning algorithms. Assess issues presented by big data in different situations. Learn essential methods, practices, and theories. Study relevant computational techniques. You’ll develop the skills and confidence you need to succeed with our Masters in data science & artificial intelligence.

Please note, there is an intake to the 12-month full-time route each September and 16-month full-time route each January. The 16-month full-time route includes the UK summer break between semesters. The part-time route takes 2-3 years to complete and typically has intakes in both September and January.

Subject to re-approval.

Course features

International students can apply

What you'll study

Artificial intelligence methods. Data mining. Virtual reality. Practical maths. Our Masters programme gives you the full skillset and experience you need to become a data scientist or analyst.

Become an expert in choosing the right tools and methods for a specific task. Study the tools and techniques for advanced analytics. Get a deep understanding of the ideas and theories behind different algorithmic artificial intelligence approaches. Learn to handle, manage, process, and analyse different kinds of data in different ways.

Help people make sense of big data sets. Learn the latest ways to share your results using graphs, pictures, and virtual reality. Explore what’s new in computing and judge its usefulness for data analysis while assessing its ethical impact. Put your knowledge into practice as you get creative to solve big data problems.

Compulsory modules:

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Advanced Professional Practice provides the opportunity to enhance your employability through activities that may include a short placement, following a live brief to complete a mini-project, undertaking a short period of study abroad, or a joint mini-project with an external partner organisation. These example activities could be in industry, related to research, or a development activity. Whether completing your activity face-to-face, virtually or a combination of the two, your chosen activity will be paired with writing a subject-specific reflective report. The module will enable you to enhance and employ a range of transferable skills, from research and analysis to teamwork, critical thinking, problem solving and reflection. You will use these skills and others to complete an individual or group project that includes the development of strategies to help determine solutions to a given scenario. You will also be encouraged to reflect on your learning journey.

Module code: CIS4509

Credits: 15

Assessment

100% Coursework

Data Mining and Visualisation immerses you in the techniques used for understanding and interpreting data to present it in a pictorial or graphical format. These approaches enable analytics to be presented visually to help aid the understanding of difficult concepts or to help identify new patterns. The human brain processes visual information 60,000 times faster than decoding text. 93% of all human communications are made up of visual content. The module will enable you to understand and interpret unstructured and diverse real-world data. You will discover how to present it visually in a quick and easy way to convey concepts in a universal manner. This will include learning cutting edge techniques in information visualisation, scientific visualisation, and visual analytics, underpinned by real-world examples and case studies. You will also have the exciting opportunity to experiment in visualising big data in our immersive virtual reality environment.

Module code: CIS4519

Credits: 15

Assessment

100% Coursework

Practical Data Analysis provides you with hands-on experience in handling, managing, processing, and analysing diverse types of data at large scale. Big data, due to its distinct characteristics, requires advanced methods for storage, transfer, handling management, analysis, and visualisation. Big data has quickly proven, however, its usefulness for making predictions and decisions in many industrial sectors. These include health, communications, manufacturing, fitness, and banking. As a result, there is significant and increasing interest in employing big data analysts in a variety of industrial sectors. The module will explore data analysis methods, data mining algorithms, visualisation techniques and advanced programming skills for data science. This will be combined with real-life big data analysis tasks. You will develop expertise in deciding which tools and methods are suitable for a large-scale data analysis task, discover how to combine them in a unified system, and determine how to implement your plan to provide a ready-to-use solution.

Module code: CIS4515

Credits: 15

Assessment

100% Coursework

How you'll study

The course is delivered through a combination of lectures, seminars, and tutorials with a mixture of daytime and evening classes. Sessions will frequently be highly interactive with a focus on the practical application of concepts and the use of case studies drawn from real life. An emphasis on small group sizes ensures that you will have plenty of opportunities for individual discussions with your tutors. Typically, you will study for approximately nine hours a week if you are studying on a full-time basis.

A full-time route, starting in either September or January, takes 12 months to complete. The part-time route takes 2-3 years to complete and typically has intakes in both September and January.

You can expect to receive your timetable at enrolment. Please note that while we make every effort to ensure that timetables are as student-friendly as possible, scheduled teaching can take place on any day or evening of the week.

How you'll be assessed

Your vocational capability, academic critical thinking and intellectual development will be assessed throughout the course. This is achieved through a combination of coursework, case studies, problem-solving exercises, and examinations. You may be assessed individually or as part of a group.

Who will be teaching you

You will be taught by highly qualified, experienced, and enthusiastic academic staff who are research-active and fully engaged with the wider business and academic community. The programme team specialise in a variety of subjects.

You will benefit from a wide range of expertise in areas such as artificial intelligence, data science, data analytics and visualisation, machine learning and deep learning, cloud/edge/distributed computing, natural language processing, computer vision, the Internet of Things, and smart devices.

There will also be occasional input from external IT professionals who will be invited to teach thematic sessions.

Entry criteria

Entry requirements

You should have a degree equivalent to UK first-class or second-class honours (2:2 or above) in a STEM discipline. This includes subjects such as computer science, computing, engineering, mathematics, science, or technology.

Equivalent knowledge gained in alternative ways, for example through professional experience or completion of BCS Professional Diploma in IT (Level 6), is also accepted.

English language requirements

International students require IELTS 6.5, with a score no lower than 6.0 in each individual component, or an equivalent English language qualification.

If your current level of English is half a band, one band, or one-and-a-half bands lower, either overall or in one or two elements, you may want to consider our Pre-Sessional English course.

How to apply

Please note, this course is now closed to international applications for 2024 entry.

There is an online application process for this course.

Please choose the application form for your preferred intake date and mode of study.

Please see our international student pages for further information about how to apply as a prospective international student.

Should you accept an offer of a place to study with us and formally enrol as a student, you will be subject to the provisions of the regulations, rules, codes, conditions and policies which apply to our students. These are available at www.edgehill.ac.uk/studentterms.

Facilities

The Department of Computer Science is based in the state-of-the-art £13million Tech Hub. This purpose-built development offers highly contemporary suites of outstanding facilities for Computer Science and Engineering students. Our modern computing and engineering laboratories are equipped with comprehensive test and measurement equipment, high-specification computers, high-resolution screens and the latest hardware and software.

A four-screen CAVE (Computer Augmented Virtual Environment) provides a super immersive 3D virtual environment, enabling users to immerse themselves in a virtual room and experience real life scenarios in 4K resolution. There are also specialist laboratories for networking and games programming, in addition to a specialist research laboratory, open access laboratory, a Harvard style lecture theatre, and ‘The Hatchery’, a working space for new business ideas.

Where you'll study

Tech Hub

Learning resources

Learning resources include robots and a robotics simulator, wired and wireless networking hardware, graphics software, web development tools, software development environments, big data servers, eye trackers, giant 3D interactive teaching screens, and other specialist software required for studying forensics and internet security techniques.

Finance

Tuition fees

£9,000

for the course

£50 per credit

for 180 credits

£16,500

for the course

EU/EEA and Swiss students who have settled or pre-settled status under the EU Settlement Scheme, as well as Irish nationals, may be eligible for the UK tuition fee rate.

Financial support

Please view the relevant Money Matters guide for comprehensive information about the financial support available to eligible UK students joining postgraduate courses at Edge Hill University.

Money Matters

EU/EEA and Swiss students who have settled or pre-settled status under the EU Settlement Scheme may be eligible to apply for financial support. Irish nationals can ordinarily apply to Student Universal Support Ireland (SUSI). If you are an EU student who does not have settled or pre-settled status, or are an international student from a non-EU country, please see our international student finance pages.

Tuition fees

£9,250

for the course

£51 per credit

for 180 credits

£17,000

for the course

EU/EEA and Swiss students who have settled or pre-settled status under the EU Settlement Scheme, as well as Irish nationals, may be eligible for the UK tuition fee rate.

Your future career

You’ll develop the skills and knowledge you need for a career in data science with our MSc Data Science & Artificial Intelligence. Apply for roles like data scientist, data analyst, big data developer or data engineer. Many industries are looking for graduates with these skills, including:

banking and finance
healthcare and pharmaceutical
telecommunications
internet and online sales
energy
cars and transport

If industry doesn’t appeal, you could create your own start up or study to PhD level like previous students.

This programme starts you on the path to chartered status.

This course has initial accreditation from BCS, The Chartered Institute for IT, on behalf of the Engineering Council, for the purposes of partially meeting the academic requirement for registration as a Chartered Engineer (subject to re-approval). It also has initial accreditation from BCS, The Chartered Institute for IT, for the purposes of partially meeting the academic requirement for registration as a Chartered IT Professional (subject to re-approval). Initial accreditation is granted to new programmes which are yet to have a graduating cohort. Successfully completing an accredited BCS course is the first step to full BCS membership and to being awarded chartered status.