The MSc in Data Science Conversion at Kingston University teaches students the full data-science toolkit — from programming and databases to analytics, machine learning and visualisation. It is designed for graduates from any discipline who want to transition into data-focused careers.
Curriculum Structure (Full-time, 1 Year)
Students begin with an intensive foundation module that introduces essential programming, statistics and data-handling skills, ensuring everyone starts at the same level. They then study Databases and Data Management, learning how to design, store and manage structured and unstructured data, alongside Applied Data Programming, where they develop practical coding and data-processing skills.
Next, they take Data Analytics and Visualisation, gaining experience in analysing datasets and presenting insights effectively, followed by Machine Learning and Artificial Intelligence, where they apply predictive models and AI techniques to real-world data. The degree concludes with a Major Project, allowing students to design and deliver a complete data-science solution from start to finish.
Focus areas: “Data management, programming, analytics, visualisation, machine learning, AI, applied project”
Learning outcomes: “Build and manage databases; write data-processing scripts; perform analytics and data visualisation; apply ML and AI models; solve end-to-end data-science problems; prepare for data-driven industry roles.”
Professional alignment (accreditation): Accredited by the British Computer Society (BCS), supporting progression toward professional IT recognition.
Reputation (employability rankings): Known for strong industry relevance and high employability, the programme prepares graduates for roles as data scientists, analysts, data engineers and ML practitioners across sectors.
The MSc Data Science at Kingston University provides practical, industry-focused skills in analysing data and building predictive models. Students apply statistical and machine learning techniques using professional software to solve real-world business and organisational problems.
Key experiential components:
Software & Tools: Hands-on data analysis using Python (Pandas, scikit-learn, TensorFlow), R, SQL, and data visualisation tools such as Tableau or Power BI.
Computing Facilities: Access to Kingston's computing labs and data science workstations equipped with the necessary software for statistical computing, machine learning, and database management.
Group Projects: Collaborative data analytics projects, often based on industry-simulated briefs, where student teams work through the full process of extracting, cleaning, analysing, and presenting insights from a complex dataset.
Applied Industry Focus: The curriculum emphasises practical application and employability. The final individual project typically involves tackling a substantial data problem, potentially in collaboration with an external organisation, to build a professional portfolio.
Graduates of Kingston University's MSc Data Science secure roles as data scientists, data engineers, machine learning engineers, and data analysts in technology, finance, healthcare, and marketing:
Careers Service offers CV workshops, placement support, employer events.
88% employment rate; average salaries £48,000–£49,000.
Industry projects with real-world data applications.
Skills for certifications in data leadership.
Outcomes in data-driven industries or research.
Further Academic Progression: Pursue PhD in data science at Kingston/elsewhere, extending dissertation project.



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