MScData Science
| Study location | 100% Online |
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| Type | Postgraduate, Online |
| Nominal duration | 2 years |
| Study language | English |
| Awards | MSc (Master of Science in Data Science) |
| Course code | INE112 |
| Tuition fee | £7,950 per programme |
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| Entry qualification | 2:2 honours degree (or higher) An Honours degree (minimum 2:2 or higher) in a relevant subject. Relevant subjects include: Computer Science, IT or other computing subjects, Maths, Statistics, any Engineering subject, any quantitative subject such as Physics, Chemistry, Business, Marketing, Economics, Psychology and Social Sciences. Experience with quantitative methods and/or coding is highly recommended. If you do not meet the above requirements but have a minimum of 12-months relevant professional experience and/or equivalent qualifications, we recommend that you apply. All applications are reviewed on a case-by-case basis. Required for your application
The entry qualification documents are accepted in the following languages: English. Often you can get a suitable transcript from your school. If this is not the case, you will need official translations along with verified copies of the original. |
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| Language requirements | English International and EU applicants are required to have a minimum overall IELTS (Academic) score of 6.5 with no component below 5.5 (or approved equivalent*). *The university accepts a large number of UK and International qualifications in place of IELTS. To find details of acceptable tests and the required grades, please visit our English Language Requirements pages. Read more on the English Language Requirements pages.A Proof of English Language Proficiency (POE) exemption may be offered to you if you meet one of the following criteria:
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| Other requirements | A motivation letter must be added to your application. We want to ensure that the programme will suit your needs, so we pay close attention to the Personal Statement which forms part of your application. Please take particular care over this statement. In a 300–500 word statement or 4-5 minute video, you should explain:
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Overview
What the world needs
The world craves data scientists: big brains to decipher big data, unlock insights and navigate an AI-fuelled future.
It’s a field that’s expected to soon make up at least a quarter of all digital jobs and has been highlighted as a major skills gap in the UK government’s recent industrial strategy.
Learn at your own pace, mastering cutting-edge skills in data management, analytics and artificial intelligence. Connect with a global network of data wizards – all from the comfort of your own home.
What this programme offers you
The MSc Data Science (online) is a flexible, industry-relevant, programme which allows you to balance your studies with professional and personal commitments. You’ll network and collaborate with a diverse cohort of students and industry experts, building connections that extend beyond geographic boundaries.
If you’re looking to specialise or upskill in this field, this master’s will equip you to apply data science techniques in your current role and organisation, or to progress onto new work opportunities.
Looking at the full data science pipeline, you’ll learn to understand organisational requirements and ethical conduct; design research studies; and employ data engineering skills to gather, transform and clean small and large-scale data.
Why choose this programme?
Educational Aims
- Gain the skills and tools to design and implement data science projects and programmes to solve real business and societal issues.
- Undertake exploratory analysis, using statistics, machine learning and predictive modelling.
- Present and communicate results to stakeholders, and become adept at implementing production workflows and solutions.
- Work on live data science projects, using data and issues from your own company (if applicable) and those of our industrial partners.
Teaching and Learning Methods
- Content is delivered through a mixture of online videos and activities as well as independent reading. You’ll have opportunities to collaborate and network with working professionals across the globe alongside a curriculum informed by the latest advancements and best practices in data science.
- With an emphasis on real-world applications of data science techniques and tools with case studies and knowledge from industry practitioners.
- Studying the role of a data scientist, you’ll become familiar with areas such as ethical practice and data for sustainable development; research methods, data gathering and exploratory data analysis; and programming principles (including R, Python, Tableau and MySQL).
- Learn to use statistical inference, modelling and analysis, machine learning and predictive analytics.
- Understand how to store, process and analyse big data. Implement data science projects from end to end, using real data to address business, health and sustainability problems.
Programme structure
Your pathway to data science expertise
The programme has a total of 180 credits. You take eight core modules; each is worth 15 credits and is an average of eight weeks in duration. Your journey culminates with your 60 credit Master’s Project.
Core Modules
Big Data (15 credits)
Understand the concepts and applications of Big Data, exploring its impact on business decision-making. Master both traditional (SQL) and alternative (NoSQL) storage approaches, gain hands-on experience with Big Data tools, and address the challenges of data quality.
Business Intelligence and Data Visualisation (15 credits)
Master the art of transforming data into actionable insights. Develop expertise in Business Intelligence tools, data visualisation techniques, and communication strategies to support effective decision-making and problem-solving in a business context.
Cloud Computing (15 credits)
Explore fundamentals of cloud computing, business applications, and security concerns. Master cloud models, enabling technologies, virtualisation, and sustainability impacts, preparing you to address challenges and leverage opportunities in this evolving field.
Data Management Fundamentals (15 credits)
Master the essential concepts and techniques for effective data management. Explore relational modelling, data querying, cleansing, NoSQL stores, architectures, and address security, environmental, and ethical considerations in data-driven environments.
Machine Learning and Predictive Analytics (15 credits)
This module equips you to mine business insights from data, using techniques like regression and random forests. Learn to visualise results, evaluate models, and navigate future trends in this software-driven field.
Process and Practice in Data Science (15 credits)
Develop the skills and ethical framework essential for successful data science projects. Master project management methodologies, explore innovation strategies, cultivate critical thinking, and address ethical considerations in a dynamic data-driven landscape.
Programming for Data Science (15 credits)
Master the fundamentals of programming in Python for data science. Learn essential concepts, data structures, and develop skills in data analysis and visualisation – ideal for both beginners and those looking to enhance their programming abilities.
Statistical Inference (15 credits)
Develop expertise in statistical inference and data analysis using R. Master reproducible research practices, data visualisation, hypothesis testing, and model building to extract valuable insights and drive evidence-based decision-making.
Final Project – Master’s Projects (60 credits)
This final project blends your technical expertise with research insights, focusing on ethics, human factors, and professional values. Produce a practical outcome like software, data analysis, or a predictive model, and showcase it in your final work.
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