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4 Years On Campus Bachelors Program
London Metropolitan UniversityThis Data Science (including foundation year) BSc (Hons) at London Metropolitan University offers a clear pathway into the field for those needing to build essential skills first, culminating in the same degree award as the standard three-year route. It’s ideal for students who want to develop strong foundations in mathematics, programming, and cyber-security before diving into advanced data science topics.
Curriculum structure
Year 1
In this preparatory year, you'll strengthen your core academic skills with modules like Cyber Security Fundamentals, Programming, Introduction to Robotics and Internet of Things, and Mathematics. These courses ensure you’re well equipped in logical thinking, basic programming, and quantitative reasoning—perfect for a smooth transition into the main degree.
Year 2
You’ll explore foundational topics such as Introduction to Information Systems, Fundamentals of Computing, Programming, Logic and Mathematical Techniques, and Data Analysis and Financial Maths. This year builds a solid technical and analytical base, helping you understand how computing systems work and how to interpret data effectively.
Year 3
Now you begin to specialise: courses include Professional Issues, Ethics and Computer Law, Databases, Data Science for Business, Data Engineering, Programming with Data, Data Analytics, and Statistical Methods and Modelling Markets. You’ll gain both the ethical perspective and technical skills—like database design, data pipelines, and statistical modelling—needed for real-world data-driven decision-making.
Year 4
You’ll cap off your studies with a Project, Artificial Intelligence and Machine Learning, Big Data and Visualisation, Work-Related Learning, and other advanced modules such as Advanced Database Systems Development, Financial Modelling and Forecasting, Formal Methods and Software Implementation, Cryptography and Number Theory, Ethical Hacking, and Academic Independent Study. This final year deepens your mastery of AI, big data tools, security, and real-world application through hands-on experience.
Focus areas
“Data programming, statistical modelling, business intelligence, machine learning, data visualisation, data engineering, analytics, big data visualisation”.
Learning outcomes
“You’ll acquire practical skills, often first-hand from an external organisation, and be able to specialise in data engineering, analytics, statistical modelling, machine learning, big data visualisation”.
Professional alignment (accreditation)
While explicit professional accreditations (like BCS or similar) aren’t mentioned in the sources, this degree is designed in close alignment with industry needs—developed by academics in mathematics and applied computing, and emphasises practical, industry-relevant tools and real-life learning.
Reputation (employability rankings)
The Teaching Excellence Framework (TEF) awarded London Met a rating in 2023 valid for four years, reflecting the university’s commitment to teaching quality. While specific QS, Guardian, or employability rankings for this program aren’t listed, external sources note career opportunities in areas like data analytics, data programming, visualization, and big data solution development, with graduates eligible for roles at companies like Facebook, Mastercard, Amazon, Microsoft, or the BBC
You'll begin with a foundation year that builds your confidence and competence, introducing core skills in mathematics, programming, cyber security, robotics, and the Internet of Things. From there, you’ll dive into real-world data science through advanced modules and the use of industry-standard software and tools.
You’ll have access to:
A wide range of up-to-date software and environments—including Spark, Kafka, Hadoop, Oracle, SQL Server, Linux, Apache Airflow, RStudio, Python (Jupyter), Tableau, and D3—enabling you to explore big data, visualization, machine learning, and beyond.
Environments for real-life case studies, where you work on authentic problems and scenarios drawn from external organisations.
A virtual learning environment (WebLearn) as well as access to library e-books and online databases, so you'll learn anytime, anywhere.
Upon graduating, you’ll be well-positioned to pursue roles in emerging data-driven fields—like Data Scientist, Data Analyst, Machine Learning Engineer, or Business Intelligence Developer—thanks to strong job-placement support, practical industry-aligned training, and real-world tools and software. Your degree also carries the credibility of a full BSc (Hons) award, whether you began with the foundation year or not.
Future Progression & Opportunities:
Which university services will help students to employ (specific information):
The university’s Careers Service and dedicated "work-related learning" module help you secure placements, client projects, and volunteering opportunities across a wide variety of organisations.
You’ll also benefit from a business incubator on campus that supports entrepreneurship and practical engagement with industry—ideal if you're considering starting your own venture.
Employment stats and salary figures:
For computing graduates at London Met, 80% are working or studying 15 months after graduation.
Average earnings stand at about £30,000 after 15 months (typical range: £27,000–£34,000).
After 5 years, average earnings rise to around £29,500 (range: £21,500–£40,000).
Within computing, 70–75% of graduates go into highly skilled roles, including IT Professionals, Science & Engineering Associate Professionals, and Business or Research roles.
Nationally, average earnings for computing graduates after 15 months are also near £30,000, with about 100% employed in England.
University–industry partnerships (specific):
As part of your degree, you’ll work with external organisations on practical skills and projects—from programming and data engineering tools to real-world case scenarios.
Long-term accreditation value:
Completing the foundation year leads into the standard Data Science BSc, awarding the exact same degree title and honour level as the traditional three-year route—ensuring full honours recognition and parity in the job market.
Graduation outcomes (job roles):
Typical roles graduates move into include Junior Data Scientist, Associate Data Analyst, Data Programming Specialist, Big Data Solution Designer or Developer.
Many graduates are placed in highly skilled IT and analytical roles—working as IT Professionals or in science, research, business, or engineering associate roles
Applicants must have completed higher secondary education equivalent to UK A-levels. Those not meeting direct entry can join via the intensive foundation year (Year 0), which leads into the BSc (Hons) Data Science. Academic transcripts/certificates are required.Non-native English speakers typically need IELTS 6.0 overall (no band below 5.5) or an equivalent test (e.g., TOEFL). Proof of English proficiency is required unless exempt through prior English-medium study.International students apply via UCAS or directly to the university, submitting transcripts, English test results, passport copy, and a personal statement (no portfolio required). Student visa applicants must study full-time, as part-time is not permitted.Data analystData scientistMachine learning engineerBusiness intelligence analystAI researcherData engineerQuantitative analystRisk analystStatisticianOperations analystResearch scientistSoftware developerDatabase administratorData consultantFinancial analystMarket researcherPolicy analystHealthcare data analystCybersecurity analystProduct analystBig data specialistCloud data engineerCustomer insights analystAcademic researcherGovernment data specialist
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