Enter OTP
This Data Science BSc (Hons) at London Met offers a hands-on introduction to essential areas like data programming, statistical modelling, business intelligence, machine learning and data visualisation, all designed by experts in both Mathematics and Applied Computing. It’s ideal for students who are curious, data-driven thinkers—inquisitive problem-solvers eager to use technology and analytics to unlock real-world insights.
Curriculum structure
Year 1
In your first year, you'll build a solid base across computing and quantitative methods, diving into modules like Data Analysis, Financial Mathematics, Fundamentals of Computing, Introduction to Information Systems, Logic and Mathematical Techniques, and Programming. You’ll develop analytical skills using statistical tools (like Excel, SPSS or R), master programming fundamentals, and begin to understand how information systems support business decision-making.
Year 2
The second year broadens your toolkit with modules such as Cloud Computing and the Internet of Things, Data Structures and Specialist Programming, Databases, Professional and Ethical Issues, Smart Data Discovery, and Statistical Methods and Modelling Markets. Here, you’ll explore how to manage data systems in the cloud and IoT environments, work with databases, learn advanced programming and data discovery, and apply statistical modeling in areas like market analysis—all with a strong ethical perspective.
Year 3
In your final year, you’ll focus on advanced topics and sharpen your real-world abilities through modules including Artificial Intelligence and Machine Learning, Career Development Learning, Data and Web Development, Formal Languages, Project, Cryptography and Number Theory, and Project Analysis and Practice. You’ll apply AI and ML techniques, develop web-based data solutions, understand formal specification, delve into cryptography, and complete a substantial individual project that ties theory to practical application.
Focus areas
Data programming; statistical modelling; business intelligence; machine learning; data visualisation
(These reflect the program’s strong applied focus, ensuring you graduate with experience in real-world tools and techniques.)
Learning outcomes
You’ll graduate with the ability to analyse and interpret complex datasets, develop data-driven solutions using programming and machine learning tools, design and deploy scalable data systems (including cloud/IoT-enabled platforms), apply modelling techniques for decision-making, and carry out independent, ethical, and professional projects.
Professional alignment (accreditation)
While specific professional accreditations aren't mentioned on the course page, the program is designed in collaboration with industry experts and places strong emphasis on professional and ethical issues—preparing you for data-science roles in business, finance, tech, or research.
Reputation (employability rankings)
The program sits within London Met’s School of Computing and Digital Media—part of a university rated in the Teaching Excellence Framework (TEF) for four years from 2023.
Though specific QS or Guardian subject rankings aren’t listed on the official page, the course is built to foster employability by emphasizing practical, industry-relevant skills and career development.
You’ll build practical, in-the-trenches skills from day one. The program trains you in the most sought-after data science platforms and programming environments—making sure you're ready to contribute from day one in your career. At the heart of your learning will be access to high-powered digital tools and the university’s own blended-learning tech, which ensure you can apply theory in real-time, supported by strong academic guidance.
And beyond software, the course offers active support through placement modules—structured as part of your academic credit, not an add-on—so you're guided into practical work environments with direct assessment and feedback.
Here’s how that translates into real resources and opportunities:
Technology tools and software environments: You’ll work with Spark, Kafka, Hadoop, Oracle, SQL Server, Linux, Apache Airflow, RStudio, Python via Jupyter, Tableau, and D3.
Blended learning infrastructure: You’ll use WebLearn (the virtual learning environment), plus the library’s e-books and online databases to engage with course materials and assessments interactively.
Work-based learning (internship) module: Option to replace one module with a university-credited internship. The Work-Based Learning team helps you find placement, liaises with employers, oversees conduct, and monitors your development.
Support for work placements: London Met’s work-placements initiative offers structured opportunities for students to engage in projects with external businesses as part of their study program.
Academic teaching and feedback structure: Expect a mix of lectures, tutorials, workshops, with tutors available for hands-on support. Coursework includes group presentations, in-class tests, exams, and practical artefacts like datasets, code, and reports—along with formative and summative feedback that helps refine your learning.
Transitioning into specifics, here’s what you’ll experience:
Software & Tools
Gain fluency in tools such as Spark, Kafka, Hadoop, Oracle, SQL Server, Linux, Apache Airflow, RStudio, Python (Jupyter), Tableau, and D3.
Digital Learning Platforms
Use the university’s WebLearn environment, access e-books and online academic databases for course content, assignments, and feedback.
Experiential Work Modules
Engage in an optional, credit-bearing internship through a Work-Based Learning module, with support from the university’s placement team.
Industry-Linked Project Experience
Participate in placement-style work with external organisations, providing project experience and professional exposure.
Tutorials, Workshops & Feedback Loops
Attend interactive tutorials and workshops alongside lectures; receive ongoing formative feedback, group presentations, and hands-on assignments to simulate real-world workflows.
London Met’s BSc (Hons) in Data Science positions graduates for strong career entry by developing practical, industry-ready skills in data programming, analytics, machine learning, and visualisation. Common roles our alumni step into include Junior Data Scientist, Data Analyst, Big Data Solution Designer, and IT/Data Consultant. These roles offer a great starting salary range (typically competitive for entry-level data professionals in London’s tech sector).
Progression & Future Opportunities:
University Services
You'll benefit from the university’s strong career-focused curriculum, which integrates work-related learning such as placements, client projects, and on-campus work experience into your studies. Additionally, graduates receive a generous 20% discount on postgraduate courses should you choose to continue at London Met.
Employment Prospects & Salary
On completion, graduates are well-prepared to enter the workforce in roles like Junior Data Scientist, Associate Data Analyst, Big Data Solution Designer, or IT/Data Consultant. Although precise graduate salary stats and salary figures aren’t publicly listed on the course page, the program’s alignment with leading tools and industry needs gives graduates a strong competitive edge.
Industry Partnerships
The course is developed with input from industry experts, ensuring the curriculum covers relevant, real-world tools and platforms such as Spark, Kafka, Hadoop, Oracle, SQL Server, Python (Jupyter), Tableau, and D3. This reflects strong engagement with industry practice and expectations. While not explicitly named, these tool integrations signal readiness for work environments using these technologies.
Accreditation & Long-term Value
While the Data Science BSc does not list an external professional accreditation, it’s built on robust academic foundations from both Mathematics and Applied Computing faculties, ensuring a respected and reliable qualification recognized across sectors. Not to mention, alumni stories reflect real confidence and success: “With London Met, I found out that – I can… I was constantly encouraged to think outside the box…”
Graduation Outcomes
Graduates of this course are not only equipped to enter industry roles but also well-prepared for further study or research, including postgraduate options in data analytics, statistics, or related areas
Minimum grade C in three A-levels or equivalent Level 3 qualifications (96 UCAS points); GCSEs (or equivalent) in English and Mathematics at grade C/4 or above; applicants with relevant professional qualifications or significant experience may also be considered.IELTS overall score of 6.0 (no component below 5.5), or equivalent PTE Academic/TOEFL scores; foundation year option available for those not meeting standard entry criteria.Applications via UCAS for full-time September entry (international applicants may also apply direct); flexible admissions considering alternative qualifications and experience; program provides a strong foundation in programming, statistical modeling, business intelligence, machine learning, and data visualization, with hands-on industry-relevant training.Data ScientistData AnalystBusiness AnalystMachine Learning EngineerArtificial Intelligence EngineerData EngineerBig Data EngineerStatisticianDatabase AdministratorQuantitative AnalystRisk AnalystFinancial AnalystOperations AnalystResearch ScientistBusiness Intelligence DeveloperData ArchitectCloud Data EngineerMarketing AnalystHealthcare Data AnalystSocial Media AnalystCybersecurity AnalystFraud AnalystProduct AnalystSupply Chain Analyst
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London Metropolitan University
