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The MSc Data Science at Lancaster University delivers advanced skills in statistics, programming (Python, R), machine learning, and artificial intelligence, tailored to industry needs. The program is ideal for graduates with quantitative backgrounds who want to gain hands-on experience in data-driven solution design, with flexible pathways in Biodiversity, Business Intelligence, or Data Engineering.
Reputation:
Lancaster University’s Data Science Institute is a UK leader in data science research, and the university is ranked in the QS Subject Rankings 51–100 for Data Science and Artificial Intelligence.
Course overview:
Core:
Fundamentals of Data Science and Artificial Intelligence
Introduction to Artificial Intelligence and Data Science
MSc Dissertation
Statistical Learning
Optional:
Advanced Topics in Artificial Intelligence
Applied Data Science for Biodiversity
Forecasting and Predictive Analytics
Geoinformatics
Intelligent Agents and Autonomous Systems
Large scale platforms for Al and Data Analysis
Natural Language Processing and Language Models
Optimisation and Heuristics
Statistical Ecology
Transportation and Logistics Analytics
Teaching methods:
Small group lectures, group-based tutorials, hands-on workshops, independent study, group projects, guest lectures, and professional skills workshops with direct industry engagement.
Assessments:
Individual and group coursework, research projects, examinations, and a major dissertation or industry placement project.
Industry projects: Real-time project work with industry partners.
Programming practice: Hands-on programming in Python and R.
Professional development: Workshops and guest lectures from experienced data science practitioners.
Advanced facilities: Access to computing labs and the Data Science Institute.
Networking opportunities: Regular events connecting students with industry professionals.
Collaborative learning: Group-based tutorials and team projects.
Research support: Structured assistance for research and professional skill-building.
Industry placement: A 14-week industry placement or academic research dissertation.
Resource access: Full use of library and digital learning resources.
Specialist pathways: Pathway-specific modules in Business Intelligence, Data Engineering, or Biodiversity.
Interdisciplinary collaboration: Opportunities to work across disciplines to broaden applied experience.
Graduate employment: Graduates are highly employable, often securing roles through their industry placements in sectors such as business intelligence, IT, life sciences, and digital innovation.
Further study: Students can pursue a PhD in Data Science, Artificial Intelligence, or related areas.
Specialist MSc options: Progression opportunities include MSc programs in Business Analytics, Computational Statistics, or Environmental Data Science, supported by the program’s applied learning focus.
Part time studies availableA 2:1 Hons degree (UK or equivalent) in any discipline, provided that the applicant has had exposure to quantitative methods such as statistics, or mathematical modelling.Applicants with a 2:2 Hons degree in Computer Science, Mathematics, Statistics, Engineering, Physics, Life Sciences, Economics, Finance and Linguistics are strongly encouraged to apply, provided that their undergraduate degree included at least one module in statistics, mathematics, mathematical modelling or machine learning (e.g. Neural networks). IELTS (Academic): Overall score of at least 6.5, and a minimum of 6.0 in each element of the test.Scholarships availableEvery student belongs to a college, and all students pay a small College Membership Fee which supports the running of college events and activities. Students on some distance-learning courses are not liable to pay a college fee.TOEFL iBT: 93 (with at least 20 in each section)Data AnalystData ScientistData EngineerData ManagerComputer Systems AnalystStatisticianBusiness Intelligence AnalystMachine Learning EngineerResearch ScientistAI Specialist
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Lancaster University
