Management and Information Systems MSc

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Our Management and Information Systems (MIS) MSc has a 30-year legacy of producing high achieving graduates who lead and shape industries worldwide. This transformative programme is renowned for its unique ability to bridge the gap between cutting-edge technology and strategic business innovation.

Tailored for aspiring leaders, the course equips students with skills in designing, managing, and optimising advanced information systems. From mastering emerging technologies like artificial intelligence, blockchain, and cloud computing to applying methodologies like Agile, DevOps, and digital transformation frameworks, students gain the tools to lead and innovate in any industry.

Over the past few years, we have offered projects with companies such as Siemens, Rolls Royce, Rolex, and others. Through case studies, real-world projects, and industrial partnerships, our students gain hands-on experience in solving complex problems and delivering impactful solutions. The course offers a robust foundation in the principles of information systems management, alongside extensive training in practical tools, methodologies, and strategies. Whether launching startups, advancing in multinational corporations, or pioneering breakthroughs in technology, our MIS MSc alumni stand at the forefront of the digital revolution, empowered by their ability to apply cutting-edge knowledge to industry challenges.

Overview

Start dateFull-time: October, part-time: throughout the year
DurationOne year full-time, Three years part-time
DeliveryTaught modules 40%, Group project 20% (dissertation for part-time students), Individual project 40%
QualificationMSc, PgDip, PgCert
SWAG合集 typeFull-time / Part-time
CampusCranfield campus

Who is it for?

Graduates eager to enhance their knowledge and skills in management and information systems, preparing for their first professional role.
Professionals with experience in technology, management, or related fields, looking to advance their careers by mastering the integration of information systems with business strategies.
Individuals seeking practical expertise, taught by faculty with real-world experience in industry and business, who bring valuable insights into the programme.

Why this course?

This programme offers deep insights into the intricate interplay of people, information, processes, and technology, empowering you to drive innovation, make data-driven decisions, and lead digital transformation efforts. With Industry 4.0 and Industry 5.0 reshaping the global landscape, this course prepares you to thrive in a world where smart factories, autonomous systems, and human-centric digitalisation are the norm.

From leveraging AI for predictive maintenance in manufacturing to deploying IoT-enabled supply chain solutions and creating immersive customer experiences using AR/VR, this programme is designed to equip you with future-ready skills. With practical applications at its core, the course positions you to excel in a wide range of domains, including research, engineering, manufacturing, production, design, consulting, and finance.

Here鈥檚 what sets this programme apart and the skills you鈥檒l gain:

Knowledge of MIS in the digital era: Learn how to seamlessly align management principles with cutting-edge technologies such as AI, IoT, Digital Twins and cloud computing. Focus on real-world applications to address dynamic industry challenges.
Expertise in digital transformation: Gain deep expertise in information systems strategy, big data management, business analytics, enterprise systems, project management, and digital transformation frameworks.
Practical, hands-on learning: Apply theories through immersive case studies, digital twins, interactive business simulations, and an industry-aligned thesis project, graduating with tangible experience in solving real-world problems using smart technologies.
Comprehensive skills development: Master tools such as data visualisation software, enterprise resource planning (ERP) systems, predictive analytics platforms, and project management software to tackle industry challenges.
Real-world focus: Engage in collaborative group projects and industry-related activities like case competitions, hackathons, and consulting assignments that mirror the demands of Industry 4.0 and Industry 5.0 workplaces.

By the end of this programme, you will have gained the knowledge and practical expertise to lead and deliver digital transformation initiatives, optimise business processes, and excel in various career paths, from consulting, to engineering and analytics to technology management and entrepreneurship. This is your opportunity to become a future-ready leader in the ever-evolving digital and information systems domain.

Informed by Industry

An external advisory panel of senior industry professionals shapes the design and development of the course, ensuring its alignment with the needs of the modern business world. Our faculty are further supported by a team of international visiting industry experts and academics who bring cutting-edge practices and the latest insights into the classroom, enriching your learning experience.

Example MIS projects and industry collaborations examples

Optimising business operations using enterprise systems (Rolls Royce): Collaborated on developing ERP (Enterprise Resource Planning) solutions for a mock manufacturing firm, using tools like SAP or Microsoft Dynamics. Delivered actionable insights into streamlining inventory, logistics, and financial processes.
AI-powered customer insights (Babcock): Designed predictive analytics models for customer behaviour in e-commerce, utilising platforms like Tableau, Python, and AWS. This project focuses on marketing optimisation and customer segmentation for improved business performance.
Data-driven cancer detection (Milton Keynes University Hospital): Partnered with teams to analyse images to identify cancer cells using advanced analytics. Applied transfer learning to enhance the decision-making process.
Smart cities IoT for urban management: Worked on IoT-enabled solutions to monitor urban utilities such as traffic, energy usage, and public safety. Use platforms like Arduino and cloud tools for prototyping and analytics.

These collaborations have allowed students a chance to gain exposure to industry challenges, learn from experienced professionals, and present real solutions to company stakeholders.

Course details

In this section

The course comprises eight assessed modules, a group project and an individual research project. The modules include lectures and tutorials, and are assessed through practical work, written examinations, case studies, essays, presentations and tests. These provide the 'tools' required for the group and individual projects.

Course delivery

Taught modules 40%, Group project 20% (dissertation for part-time students), Individual project 40%

The group project experience is highly valued by both students and prospective employers. Teams of students work to solve an industrial problem. The project applies technical knowledge and provides training in teamwork and the opportunity to develop non-technical aspects of the taught programme. Part-time students can prepare a dissertation on an agreed topic in place of the group project.

Industrially orientated, our team projects have support from external organisations. As a result of external engagement Cranfield students enjoy a higher degree of success when it comes to securing employment. Prospective employers value the student experience where team working to find solutions to industrially based problems are concerned.

A key element of the Master's programme is the project work undertaken.

The individual research project is either industrially or SWAG合集 driven. Students select the individual project in consultation with the Course Director. It provides students with the opportunity to demonstrate independent research ability, the ability to think and work in an original way, contribute to knowledge, and overcome genuine problems in manufacturing. The projects are sponsored by industrial organisations.

Companies that have recruited and sponsored project work include 3M Health Care, Airbus, Aston Martin, BAE Systems, BT, Chubb Security, Ford Motor Company, GEC, GlaxoSmithKline, IBM, Jaguar, Johnson & Johnson, Motorola, Pfizer, Philips, Rolls-Royce and Unilever.

Modules

Keeping our courses up-to-date and current requires constant innovation and change. The modules we offer reflect the needs of business and industry and the research interests of our staff and, as a result, may change or be withdrawn due to research developments, legislation changes or for a variety of other reasons. Changes may also be designed to improve the student learning experience or to respond to feedback from students, external examiners, accreditation bodies and industrial advisory panels.

To give you a taster, we have listed the compulsory and elective (where applicable) modules which are currently affiliated with this course. All modules are indicative only, and may be subject to change for your year of entry.

Course modules

Compulsory modules
All the modules in the following list need to be taken as part of this course.

Aim	To introduce you to the core factors of managing operations and the concept of flow in operations.
Syllabus	• An introduction to manufacturing organisations and functions. • The theory of operations, flow in manufacturing and what enables/inhibits it. • Order winners, Order qualifiers, and competitive priorities. • Key Performance Indicators in manufacturing. • Product/Process matrix, facility layouts, production strategies, product families. • Customer Demand and capacity planning, and standardization. • Process flow diagrams, and value stream maps. • S&OP, Master Production Scheduling, BOM, and scheduling rules. • Push vs Pull production. • Information systems; MRP, MPRll, ERP, and Kanban systems. • Maintenance management strategies. • Dimensions of Quality, Quality management frameworks, and the cost of quality. • Roles of inventory; inventory management systems and measures. • Lean Manufacturing. • Class discussion of cases, exercises, and videos to support this syllabus.
Intended learning outcomes	On successful completion of this module you will be able to: 1. Discuss the importance of the operations functions of an organisation and how operations performance can impact the success of the whole organisation. 2. Assess production and capacity management strategies that can be deployed to meet customer demand for products and services. 3. Assess the importance of inventory, maintenance, and quality management systems in achieving high levels of operational performance. 4. Determine the role of information in planning, control, and scheduling, including the role of IT systems. 5. Critique the different attributes of the Lean Production System and how they apply to contemporary operational contexts.

Aim

To introduce you to the core factors of managing operations and the concept of flow in operations.

Syllabus

• An introduction to manufacturing organisations and functions.

• The theory of operations, flow in manufacturing and what enables/inhibits it.

• Order winners, Order qualifiers, and competitive priorities.

• Key Performance Indicators in manufacturing.

• Product/Process matrix, facility layouts, production strategies, product families.

• Customer Demand and capacity planning, and standardization.

• Process flow diagrams, and value stream maps.

• S&OP, Master Production Scheduling, BOM, and scheduling rules.

• Push vs Pull production.

• Information systems; MRP, MPRll, ERP, and Kanban systems.

• Maintenance management strategies.

• Dimensions of Quality, Quality management frameworks, and the cost of quality.

• Roles of inventory; inventory management systems and measures.

• Lean Manufacturing.

• Class discussion of cases, exercises, and videos to support this syllabus.

Intended learning outcomes

On successful completion of this module you will be able to:

1. Discuss the importance of the operations functions of an organisation and how operations performance can impact the success of the whole organisation.

2. Assess production and capacity management strategies that can be deployed to meet customer demand for products and services.

3. Assess the importance of inventory, maintenance, and quality management systems in achieving high levels of operational performance.

4. Determine the role of information in planning, control, and scheduling, including the role of IT systems.

5. Critique the different attributes of the Lean Production System and how they apply to contemporary operational contexts.

Aim	This module aims to provide a systematic understanding and knowledge of key concepts and principles for digital engineering and its current practices, tools and processes and future development. The course will also provide hands-on experience using digital engineering tools and methods using examples from product and service development.
Syllabus	• Introduction to Digital Engineering concepts. • Digital Engineering Tools and Methods. • Internet of Things (IoT), Virtual and Augmented Reality (VR&AR). • Digital Twins. • Artificial intelligence and machine learning. • Digital Engineering Industrial Case Studies.
Intended learning outcomes	On successful completion of this module, you will be able to: 1. Evaluate the principles of digital engineering, its applications and benefits in product and service development. 2. Critically evaluate the selection of digital engineering tools and methods. 3. Create digital engineering tools and techniques in areas such as product and service development. 4. Critically evaluate the process of developing and using Virtual and Augmented Reality (VR&AR) methods and tools. 5. Evaluate the challenges in digital engineering implementation in industry.

Aim

This module aims to provide a systematic understanding and knowledge of key concepts and principles for digital engineering and its current practices, tools and processes and future development. The course will also provide hands-on experience using digital engineering tools and methods using examples from product and service development.

Syllabus

• Introduction to Digital Engineering concepts.

• Digital Engineering Tools and Methods.

• Internet of Things (IoT), Virtual and Augmented Reality (VR&AR).

• Digital Twins.

• Artificial intelligence and machine learning.

• Digital Engineering Industrial Case Studies.

Intended learning outcomes

On successful completion of this module, you will be able to:

1. Evaluate the principles of digital engineering, its applications and benefits in product and service development.

2. Critically evaluate the selection of digital engineering tools and methods.

3. Create digital engineering tools and techniques in areas such as product and service development.

4. Critically evaluate the process of developing and using Virtual and Augmented Reality (VR&AR) methods and tools.

5. Evaluate the challenges in digital engineering implementation in industry.

Aim	This module will provide the processes to design and develop artificial intelligence (AI) based approaches to be trained for data analytics on a spectrum of data types (e.g. messy data, data gaps or big data), whilst also considering the ethical implications.
Syllabus	Theory of data analytics, AI, ML, data mining, statistics and supervised learning, e.g., probability, decision trees, regression and classification. Experience of real-world AI/ML applications, in areas such as engineering, business, social media, medical data and financial data. Evaluate alternative ethical considerations including human-machine collaboration that are related to the use of AI/ML. The opportunity to work on industry problems that can benefit from AI/ML approaches.
Intended learning outcomes	On successful completion of this module you should be able to: Compare and contrast data analytics methods including machine learning (ML) in terms of its current and future concepts, principles and theories. Construct ML concepts and methods to impart innovative problem-solving skills in a variety of data maturity scenarios. Evaluate value creation opportunities from ML, develop value propositions and revenue models for businesses and organisations. Construct data analytics-based methods for real world problems with the changing nature of digital technology infrastructure and varying volume and quality of data. Appraise ethical responsibility considering human-machine collaboration in data analytics by reflecting on intelligent systems that benefit society.

Aim

This module will provide the processes to design and develop artificial intelligence (AI) based approaches to be trained for data analytics on a spectrum of data types (e.g. messy data, data gaps or big data), whilst also considering the ethical implications.

Syllabus

Theory of data analytics, AI, ML, data mining, statistics and supervised learning, e.g., probability, decision trees, regression and classification.
Experience of real-world AI/ML applications, in areas such as engineering, business, social media, medical data and financial data.
Evaluate alternative ethical considerations including human-machine collaboration that are related to the use of AI/ML.
The opportunity to work on industry problems that can benefit from AI/ML approaches.

Intended learning outcomes

On successful completion of this module you should be able to:

Compare and contrast data analytics methods including machine learning (ML) in terms of its current and future concepts, principles and theories.
Construct ML concepts and methods to impart innovative problem-solving skills in a variety of data maturity scenarios.
Evaluate value creation opportunities from ML, develop value propositions and revenue models for businesses and organisations.
Construct data analytics-based methods for real world problems with the changing nature of digital technology infrastructure and varying volume and quality of data.
Appraise ethical responsibility considering human-machine collaboration in data analytics by reflecting on intelligent systems that benefit society.

Aim	To develop your understanding and practice of business data analytics to describe, predict, and inform business decisions.
Syllabus	• Information-based decisions. • Basic Data Analytics. • Usage of Tools for Data Modelling, Management and Analysis. • Data quality and system interoperability.
Intended learning outcomes	On successful completion of this module you should be able to: 1. Distinguish the types of data typical in business management. 2. Construct data models from datasets representative of data extracted from business IT systems. 3. Evaluate reliability of datasets and devise ways to enhance trustworthiness of data extracted from business IT systems. 4. Analyse and investigate patterns from datasets representative of data extracted from business IT systems. 5. Present data analysis results to support management decisions.

Aim	To extend your ability to evaluate complex systems within the context of the wider enterprise environment through the application of modelling and simulation tools, techniques and methodologies.
Syllabus	• Introduction to modelling: taxonomy, overview of methods and techniques. • Enterprise Modelling. • Process description capture tools and techniques. • Discrete-event simulation, Systems dynamics and Agent-based simulation techniques and methodologies. • Case study analysis, use of industry-based software tools.
Intended learning outcomes	On successful completion of this module you should be able to: 1. Distinguish the concepts related to modelling approaches. 2. Analyse challenges and opportunities in the capture and representation of business knowledge through modelling. 3. Critically evaluate the opportunities in a business and industrial processes where modelling and simulation can add value. 4. Construct and apply different modelling & simulation approaches used in complex systems.

Aim

To extend your ability to evaluate complex systems within the context of the wider enterprise environment through the application of modelling and simulation tools, techniques and methodologies.

Syllabus

• Introduction to modelling: taxonomy, overview of methods and techniques.

• Enterprise Modelling.

• Process description capture tools and techniques.

• Discrete-event simulation, Systems dynamics and Agent-based simulation techniques and methodologies.

• Case study analysis, use of industry-based software tools.

Intended learning outcomes

On successful completion of this module you should be able to:

1. Distinguish the concepts related to modelling approaches.

2. Analyse challenges and opportunities in the capture and representation of business knowledge through modelling.

3. Critically evaluate the opportunities in a business and industrial processes where modelling and simulation can add value.

4. Construct and apply different modelling & simulation approaches used in complex systems.

Aim	鈥嬧€婽he module aims to provide a systematic understanding and knowledge of the enterprise systems principles and how to use these systems to manage an enterprise. The course will also provide hands-on experience using SAP as a leading industry-standard software application 鈥嬧€�
Syllabus	• Introduction to business functions, processes and data requirements within an enterprise. • Enterprise wide IT systems. Managing Enterprise through ERP. • Enterprise Resource Planning (ERP): concepts, techniques and tools. • ERP selection and implementation issues. • An Introduction to IoT and Cyber Security. • SAP based hands-on case studies.
Intended learning outcomes	On successful completion of this module you will be able to: 1. Distinguish the principles of business functions, processes and information management. 2. Examine the concepts, tools and techniques of Enterprise Resource Planning (ERP) and the criteria for ERP selection. 3. Evaluate issues and challenges in ERP implementation and the importance of Enterprise-wide systems to business operations. 4. Appraise Enterprise Systems Operations and Support and related subjects such as IoT and Cyber Security. 5. Demonstrate working/application knowledge on the use of SAP tool through hands-on case studies.

Aim

鈥嬧€婽he module aims to provide a systematic understanding and knowledge of the enterprise systems principles and how to use these systems to manage an enterprise. The course will also provide hands-on experience using SAP as a leading industry-standard software application 鈥嬧€�

Syllabus

• Introduction to business functions, processes and data requirements within an enterprise.

• Enterprise wide IT systems. Managing Enterprise through ERP.

• Enterprise Resource Planning (ERP): concepts, techniques and tools.

• ERP selection and implementation issues.

• An Introduction to IoT and Cyber Security.

• SAP based hands-on case studies.

Intended learning outcomes

On successful completion of this module you will be able to:

1. Distinguish the principles of business functions, processes and information management.

2. Examine the concepts, tools and techniques of Enterprise Resource Planning (ERP) and the criteria for ERP selection.

3. Evaluate issues and challenges in ERP implementation and the importance of Enterprise-wide systems to business operations.

4. Appraise Enterprise Systems Operations and Support and related subjects such as IoT and Cyber Security.

5. Demonstrate working/application knowledge on the use of SAP tool through hands-on case studies.

Aim	To introduce you to the wider issues surrounding the management and optimisation of supply chains.
Syllabus	Supply chain concepts Supply chain strategy Relationship management Supplier Selection and Evaluation Supplier Sustainability Supply chain Planning Design & Operating SC Outsourcing Product Design and Manufacturing
Intended learning outcomes	On successful completion of this module you will be able to: 1. Evaluate issues surrounding the development of the right supply chain strategy for the business / product groups. 2. Create strategies for managing the information flows in a supply network in order to reduce the bullwhip effect and the challenges of accurate demand and forecast planning. 3. Evaluate the challenges with improving performance of supply networks and gain familiarity with the application of a variety of supply chain tools to help in the re-design of the SC. 4. Apply criteria in the sourcing, evaluation and validation of suitable providers of parts, design and manufacturing services for the supply of a complex engineered product. 5. Integrate procurement and supplier management for the supply chain to function effectively.

Aim

To introduce you to the wider issues surrounding the management and optimisation of supply chains.

Syllabus

Supply chain concepts
Supply chain strategy
Relationship management
Supplier Selection and Evaluation
Supplier Sustainability
Supply chain Planning
Design & Operating SC
Outsourcing Product Design and Manufacturing

Intended learning outcomes

On successful completion of this module you will be able to:

1. Evaluate issues surrounding the development of the right supply chain strategy for the business / product groups.

2. Create strategies for managing the information flows in a supply network in order to reduce the bullwhip effect and the challenges of accurate demand and forecast planning.

3. Evaluate the challenges with improving performance of supply networks and gain familiarity with the application of a variety of supply chain tools to help in the re-design of the SC.

4. Apply criteria in the sourcing, evaluation and validation of suitable providers of parts, design and manufacturing services for the supply of a complex engineered product.

5. Integrate procurement and supplier management for the supply chain to function effectively.

Aim	This module provides the skills to design and develop integrated data management approaches and systems to address data related challenges. This includes managing large volumes of data from disparate sources, identifying and resolving data quality issues, handling disparate data lacking integration and generating insights for agile decision making that are integrated in terms of their data, models and visualisation for agile decision making.
Syllabus	Introduction to software programming with a view to developing data management systems. Evaluate existing standards related to data management. Apply methods for data needs analysis. Establish mechanisms for enabling connectivity of data acquired from alternative sources – e.g. people, sensors, 5G, IoT. Develop data structures and approaches to data modelling using ontologies and reference architectures.
Intended learning outcomes	On successful completion of this module you should be able to: Assess the system requirements for the integration and accessibility of data to deliver value in complex systems. Critically evaluate existing approaches to acquire data from fixed and mobile sources. Appraise strategies and techniques to measure and optimise the quality of data. Construct efficient data structures enabled by ontologies and reference architectures to allow continuous and standardised data flow. Justify mechanisms for allowing connectivity of data to enable links to models and visualisation platforms.

Aim

This module provides the skills to design and develop integrated data management approaches and systems to address data related challenges. This includes managing large volumes of data from disparate sources, identifying and resolving data quality issues, handling disparate data lacking integration and generating insights for agile decision making that are integrated in terms of their data, models and visualisation for agile decision making.

Syllabus

Introduction to software programming with a view to developing data management systems.
Evaluate existing standards related to data management.
Apply methods for data needs analysis.
Establish mechanisms for enabling connectivity of data acquired from alternative sources – e.g. people, sensors, 5G, IoT.
Develop data structures and approaches to data modelling using ontologies and reference architectures.

Intended learning outcomes

On successful completion of this module you should be able to:

Assess the system requirements for the integration and accessibility of data to deliver value in complex systems.
Critically evaluate existing approaches to acquire data from fixed and mobile sources.
Appraise strategies and techniques to measure and optimise the quality of data.
Construct efficient data structures enabled by ontologies and reference architectures to allow continuous and standardised data flow.
Justify mechanisms for allowing connectivity of data to enable links to models and visualisation platforms.

Teaching team

You will be taught by leading academics and experienced practitioners in change management and IT drawn from Cranfield鈥檚 network of partners. The course is directed by an industrial advisory committee comprising senior representatives from leading manufacturing and business organisations. This means the skills and knowledge you acquire are relevant to employer requirements. The Course Director for this programme is Dr Samir Khan.

SWAG合集 really helps you explore what you don't know and the support that the academic professors have given has been fantastic. The industrial partners you will be engaging with are also fantastic.

The exceptional academic staff, state-of-the-art facilities and additional resources provided throughout the course highly contributed to an amazing academic year with top-level education services.

I chose to study at SWAG合集 as I felt like I had a strong affinity for the Management and Information Systems MSc. I became aware of SWAG合集 through hearing the experiences shared by former students who chose to pursue further studies here at SWAG合集.

SWAG合集 empowers me to attain technical proficiency in Information Technology and vocational stability in Manufacturing. Coming from a background in Library Science, I never imagined achieving such a significant milestone. However, Cranfield has equipped me and broadened my horizons of thought. This has definitely been a highlight from my time here at Cranfield.

Accreditation

The MIS MSc course is accredited by prestigious professional bodies, including the , the , and .

These accreditations ensure that the course meets high industry standards and enhances your professional recognition. As a student, you will have the opportunity to engage with a curriculum aligned with the competencies valued by these organisations, equipping you with the skills to pursue professional qualifications in management, information systems, and related fields. These accreditations also provide a pathway to becoming a Chartered Engineer (CEng) or Chartered IT Professional (CITP), depending on your career goals.

Please note accreditation applies to the MSc award, PgDip and PgCert (if offered) do not meet in full the further learning requirements for registration as a Chartered Engineer.

Your career

Graduates of the MIS MSc course are highly sought after by employers across a wide range of industries, including technology, consulting, finance, healthcare, and manufacturing. Typical job roles include IT Manager, Business Analyst, Data Analyst, Systems Consultant, Enterprise Architect, and Project Manager. Many graduates find opportunities with leading multinational companies such as Rolls Royce, BAE Systems, Babcock International, Accenture, Deloitte, PwC, Google, Microsoft, and Siemens, as well as innovative startups and government organisations.

With a strong foundation in managing information systems and aligning them with business strategies, MIS graduates are well-equipped to drive digital transformation and contribute to organisational success in the rapidly evolving global job market.

Cranfield’s Career Service is dedicated to helping you meet your career aspirations. You will have access to career coaching and advice, CV development, interview practice, access to hundreds of available jobs via our Symplicity platform and opportunities to meet recruiting employers at our careers fairs. Our strong reputation and links with potential employers provide you with outstanding opportunities to secure interesting jobs and develop successful careers. Support continues after graduation and as a Cranfield alumnus, you have free life-long access to a range of career resources to help you continue your education and enhance your career.

Part-time route

Pursue your MSc degree with us and advance your career without putting your professional life on hold. Our part-time study option for the Management of Information Systems MSc is designed for professionals who are keen to enhance their career prospects without pausing their full-time employment. We understand the importance of maintaining a work-life-study balance and have tailored our program to ensure you can achieve this with minimal disruption.

What we offer to Part-Time students:

Manageable study schedule: The part-time format is structured to blend effectively with your professional life, offering the full spectrum of learning opportunities and facilities accessible to all our students.

Global accessibility: Our university’s prime location makes it an ideal choice for visiting part-time students from across the globe. You’ll also have access to our extensive range of library resources and support facilities to aid your studies.

On-campus teaching blocks: As a part-time student, you will attend on-campus teaching in one-week blocks, totalling 8 blocks over the 2 – 3 year duration of the course. These teaching blocks are typically scheduled from October to March, allowing you to plan your schedule well in advance.

Flexible study and project work: Following the teaching blocks, you will engage in independent study and project work. This phase offers flexibility, with the option for in-person or online interactions with your supervisors and peers.

Intake Options for Diverse Needs: Students aiming for the MSc degree will begin their studies in the October intake. Those opting for the research focused MRes have the additional option to commence either in October or January.

We believe this structure provides the perfect balance, allowing you to manage your time effectively between work, study, and family commitments.

Click on the ‘Apply now’ button below to start your online application.

See our Application guide for information on our application process and entry requirements.