MSc Applied Data Science (Part-time, Online)
Advance the technical expertise and professional development you need for a successful career in the evolving sector of data science.
About the course
The MSc in Applied Data Science is a two-year, online, part-time taught programme designed to develop the advanced skills needed for you to thrive in the rapidly evolving field of data science. Whether you want to become a data scientist, develop expertise in AI and analytics, lead data-driven decision-making, or progress into research, the MSc Applied Data Science can help you take the next step in your career.
Data Science has emerged as a vital scientific discipline with transformative applications across sectors such as Finance, Healthcare, Education, Information Technology, Insurance, Retail, Transport, and Utilities. As organisations increasingly rely on complex data to understand behaviours, improve strategic decisions and drive innovation, demand is growing for professionals with advanced expertise in data mining, machine learning, AI and data analytics who could deliver data-driven transformations.
Combining technical expertise with analytical, leadership and professional development, this master’s degree prepares graduates and experienced practitioners alike to turn complex data into actionable insights, create organisational value and contribute to strategic decision-making.
A distinctive feature of the programme is its integration of knowledge and skills in leadership, technology innovation and enterprise, ethics, and research. These are developed through workshops led by experts from the University and industry.
The programme balances theory with practical application, developing your critical understanding, technical expertise, innovation and transferable skills for applying data science effectively in professional settings.
The School of Computing’s Industry Advisory Board is foundational to our curriculum development, and we work closely with board members to co-design our programmes and refine our courses in response to real-world demands.
The programme is further enriched by contributions from industry practitioners and external experts. Their first-hand experience provides you with current perspectives on industry practice, emerging technologies and real-world challenges, helping to connect academic learning with professional practice.
Who is the programme for?
We welcome applicants from diverse backgrounds, including:
- International students seeking flexible, part-time online study without relocating to the UK.
- UK and overseas professionals looking to upskill or reskill in data science while continuing their employment.
- Experienced professionals seeking a formal academic qualification to complement the knowledge and skills gained through their work experience.
How is the programme delivered?
- The course is taught entirely online.
- An induction session at the start of the programme.
- Flexible, self-paced study materials designed around your schedule.
- Live online weekly interactive sessions – one afternoon session per week.
- Academic support via 1:1 meetings with your module lead.
- Project support with 1:1 meetings with your academic supervisor.
Course Highlights
- Develop end-to-end data science expertise to achieve strategic business objectives.
- Explore advanced and emerging AI applications shaping modern data-driven systems.
- Develop technology leadership skills, including team management, communication, digital transformation, ethics and innovation.
- Complete a substantial individual capstone project, applying the knowledge and skills to a real-life complex data science problem.
- Learn flexibly through self-paced study materials, complemented by live weekly online sessions with expert academic staff.
Course breakdown
This two-year programme builds technical mastery, strategic leadership, and practical problem-solving across six terms. Please find further details about the programme breakdown in the Curriculum Handbook, below.
The programme is intentionally structured to build from foundational knowledge and skills to advanced application through four taught modules (30 credits each) and an individual capstone project (60 credits).
- You will begin by establishing a strong foundation in advanced scripting, mathematics and machine learning, alongside research methods, professional practice and leadership skills to support data-driven transformation.
- This is followed by exploration of the data science lifecycle through the CRISP-DM framework and development of advanced techniques in deep learning and artificial intelligence, with a focus on their application in data science.
- The degree culminates in an individual capstone project that brings together the knowledge and skills developed throughout the programme to deliver an end-to-end data science solution to a real-world problem.
View course modules
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Teaching and assessment
We keep class sizes small so you won’t get lost in the crowd. You will be assigned a personal tutor to support you every step of the way, and our academic and student support teams will ensure you have the tools to succeed in your studies. We value the quality of your learning experience.
Teaching methods
The MSc in Applied Data Science is delivered through a flipped learning approach, combining self-directed study with live interactive teaching:
- Self-paced guided learning: Teaching materials, including lecture slides, reading materials and recommended books, and practical worksheets, are provided at the start of each module. These resources enable you to study independently at your own pace.
- Live online interactive sessions: Weekly interactive sessions are delivered via Microsoft Teams, giving you the opportunity to complete practical activities and have engaging discussions and communicate with academics as needed.. All live online sessions are recorded: This allows you to access sessions at a time and pace that suits your individual needs.
- Seminars and hands-on workshops: You will also benefit from our engaging seminars and workshops, with guest speakers from academia and industry, delivering their content online for you to join..
- One-to-one project supervision: Individual supervision provides personalised academic and practical guidance throughout the capstone project.
Our teaching is enhanced by virtual learning environments, learning tools and software packages. A state-of-the-art room is available for lecturers to conduct live online teaching and to record lecture material.
It is also our core principle to remain accessible to students beyond scheduled teaching sessions, fostering supportive and constructive relationships between staff and students.
Enrichment activities
The School of Computing hosts a Computing Seminar series throughout the year for all its staff, students and apprentices. Approximately 24 seminars are held per year (January – December). These seminars are given by industry experts, academics from other HEIs and postgraduate research students in computing. The seminars cover a wide range of topics related to the latest developments and emerging trends in computing.
Teaching team
Our academic team is approachable, diverse, and highly qualified, with expertise in AI, computing, data science, and mathematics. All of our academics are research active, and many of whom have worked with business and industry partners on real IT projects and have successfully supervised a range of Level 7 data science projects. Several academics hold a teaching qualification (Fellow or Senior Fellow or Advanced HE). Nearly all have a PhD in Computing or Mathematics.
In addition to the academic team of the School of Computing at Buckingham, high-profile guest lecturers and speakers from academia and industry are invited to deliver seminars and workshops on a range of topics covered in the programme.
Assessment Methods
A range of assessment techniques are utilised throughout the degree programme to allow you to demonstrate achievement of the learning outcomes.
The assessment of individual modules within each programme varies according to the subject. Please check the module information for more details.
Examples of the assessment methods of the programme include:
- Practical coursework
- Research report/Dissertation
- Reflective statement
- Portfolio
- Multiple Choice Quiz (MCQ)
- Project proposal
- Project practical work
- Project report
- Viva & Presentation.
The MSc programme is assessed and graded according to the details in the programme and module specifications following the University’s Regulations.
The standards of degrees and awards are safeguarded by distinguished external examiners – senior academic staff from other universities in the UK – who approve and moderate assessed work. The quality of teaching, learning and assessments are continuously enhanced through peer-observation, feedback, and continuous professional development activities.
After your course
Graduating from our MSc Applied Data Science degree, you will be well-equipped to pursue data-driven careers across technology, business, healthcare, finance, insurance, academia and many other sectors.
Our graduates have gone on to build successful careers in a wide range of roles and organisations, including:
- Public sector: Clinical Data Coordinator, Associate Data Engineers at the NHS
- Industry: Data Engineer at Jaguar Land Rover, Senior BI Consultant at Lloyds, and Clinical Data Manager at Vitalograph
- Academia: Lecturer, Learning Development Coach in Data Science, with some graduates progressing to PhD study at The University of Buckingham
Other senior roles held by our graduates include Business Intelligence Manager, Senior Business Analyst and Business Engagement Lead, and Operations & Data Analytics Specialist.
Our Careers and Employability Service is here to support you beyond the classroom, helping you develop your professional portfolio, strengthen your employability skills and build connections with employers. Find out more about our Careers and Employability Service.
Here are just some of the career opportunities and skills that can stem from studying on this course:
Career opportunities
- Data scientist
- Data analyst
- Business Intelligence Analyst
- Data Engineer
- Machine learning engineer
- AI/Machine Learning Specialist
- Data strategy and digital transformation leader
- Data Science Consultant.
Career skills
- Data-driven solution design and implementation
- Technical expertise and proficiency in Python
- Machine learning and AI application
- Critical thinking and problem-solving
- Self-direction and reflective learning
- Effective Project Management & leadership
- Effective communication and data storytelling
- Making sound and data-informed business decisions.
Careers and Employability Support
Our courses strive to effectively combine academic challenge with the transferable skills that will stand you in good stead for future employment. The Buckingham tutorial teaching model means that our students are well prepared as they embark on their careers and future study.
Find out more about our Careers and Employability Service.
Further study
Further your expertise in your field of study with our doctoral degrees.
“Upon completing my postgraduate degree, I have undoubtedly obtained the necessary independent and research skills to embark on my professional journey. The extensive knowledge I have acquired through this advanced degree sets me apart from other candidates, giving me a distinct advantage.”
Eleanor, Postgraduate student
Entry requirements
See our general University entry requirements for information on flexible entry, mature students and alternative qualifications.
The standard entry requirements for this course are:
- An undergraduate degree at 2:1 or higher in a STEM subject (Computing, Engineering, Physics or Mathematics).
- Relevant work experience may be considered instead of a STEM degree.
- If your first language is not English, you will also need an IELTS score of 6.5 with at least 6.0 in each component.
Applicants must also have:
- Fundamental programming skills.
- A good background in mathematics.
International Applicants
We are happy to consider all international applications. If you are an international student, you may find it useful to visit our international pages for details of entry requirements from your home country.
Find out about our requirements and see useful information for international applicants:
If you are uncertain whether you will be eligible to apply for this course, please contact our Admissions team.
Course fees
The fees for this course are:
| Start | Type | 1st Year | Total cost |
|---|---|---|---|
Month Year Full-time (2 Years) | UK | £00,000 | £00,000 |
| INT | £00,000 | £00,000 | |
Month Year Full-time (2 Years) | UK | £00,000 | £00,000 |
| INT | £00,000 | £00,000 |
Where courses exceed one year in duration, the University reserves the right to increase course fees annually in line with inflation linked to the Retail Price Index (RPI). If the University intends to increase your course fees it will notify you via email of this as soon as reasonably practicable.
Course fees do not include additional costs such as books, equipment, writing up fees and other ancillary charges. Where applicable, these additional costs will be made clear.
Scholarships and bursaries
How to apply
Apply direct
Apply online from this page as:
- You can apply until shortly before the course starts.
- There are no application fees.
You can apply directly through our website by clicking the ‘Apply Now’ button.