

MSc Data Science
- Time investment
- 2 years part-time
- Location
- Online
- Cost
- £9,000
- Language
- English
About this degree
Advance your career with essential data science skills for the future
Elevate your career potential with the University of Roehampton’s MSc Data Science – a programme tailored for the innovators of tomorrow. Immerse yourself in a comprehensive curriculum designed to equip you with cutting-edge analytical skills and actionable industry insights.
Enhance your analytical skills with advanced data analytics
You’ll start by building a solid foundation in data analytics, focusing on essential techniques and methodologies for effective data interpretation. This section enables you to refine your ability to analyse and interpret data, providing the groundwork for tackling complex data-driven challenges in various professional settings.
Explore real-world applications of machine learning
Progressing from foundational analytics, you’ll delve into machine learning algorithms and their practical applications. Engage with real-world case studies as you design and implement machine learning models that identify patterns and predictions, equipping you with the hands-on skills crucial for tackling industry-specific challenges.
Develop ethical data solutions across interdisciplinary fields
Next, you’ll learn to construct responsible data solutions, integrating a comprehensive understanding of ethical considerations. This approach ensures you’re prepared to apply data science techniques across various domains, with a keen awareness of societal impacts.
In wrapping up this intensive programme, you’ll consolidate your skills through a hands-on capstone project, applying theoretical knowledge to practical scenarios. This knowledge culminates in a robust foundation that prepares you to lead in the dynamic and constantly evolving field of data science, poised with the tools to make meaningful contribution.
Grow online with industry experts at the University of Roehampton
Roehampton’s Online MSc Web Development programme is designed for the everyday working professional. No matter where you are in the world, you’ll progress your studies – and career – with flexible online learning options that fit seamlessly into your busy schedule.
Where you’ll be studying

Studying at the University of Roehampton
University of Roehampton is where ambition meets opportunity.
Expert-led programmes with industry-focused curricula challenge up-and-coming professionals to think critically, explore new ideas, and develop the expertise needed for career growth.
With flexible learning environments and on-demand support, Roehampton empowers you not just to adapt to changing industries but to drive innovation within them.
Learning outcomes
Cultivate essential skills in examining diverse datasets, utilising programming algorithms and descriptive statistics to draw meaningful conclusions.
Develop expertise in applying machine learning techniques, including decision trees and neural networks, to solve complex problems and evaluate system performance.
Acquire the mathematical skills necessary for data science, focusing on statistics, probabilities, and linear algebra to formulate and analyse data-driven solutions.
Investigate real-life applications of deep learning, gaining insights into technologies that drive innovation in various industries.
Analyse the transformative impact of data science applications in sectors like marketing and healthcare, gaining hands-on experience with leading frameworks.
Create engaging visual representations of data by applying principles of design and cognitive science, while integrating web development techniques for interactive delivery.
Find out more about this degree
Additional information
- IELTS Academic – 6.5 overall
- Roehampton’s English Language Test – 6.5 overall
- Kaplan Test of English – 478-509 overall
- TOEFL IBT – 89 overall
- PTE Academic – 59 overall
- Cambridge – 176 overall
- Data Scientist
- Data Analyst
- Machine Learning Engineer
- Business Intelligence Analyst
- Data Engineer
- Quantitative Analyst
- Academic qualifications (certificate or transcript)
- Valid English language qualification
- Personal statement
- Two references
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