Data Science BSc Hons

3 Years On Campus Bachelors Program

London Metropolitan University

Program Overview

This Data Science BSc (Hons) at London Met gives you a hands-on introduction to the core areas of the field—data programming, statistical modelling, business intelligence, machine learning, and data visualisation. Developed by experts in Mathematics and Applied Computing, the course is perfect for curious, data-driven thinkers—problem-solvers eager to use technology and analytics to uncover real-world insights.

Curriculum Structure

Year 1
In your first year, you’ll lay a strong foundation across computing and quantitative methods. Core modules include Data Analysis, Financial Mathematics, Fundamentals of Computing, Introduction to Information Systems, Logic and Mathematical Techniques, and Programming. You’ll start developing analytical skills with tools like Excel, SPSS, or R, learn the fundamentals of programming, and understand how information systems support business decisions.

Year 2
Your second year expands 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. You’ll gain experience managing data in cloud and IoT environments, work with databases, explore advanced programming and data discovery techniques, and apply statistical modeling to real-world problems like market analysis—all while keeping ethical considerations front and center.

Year 3
In your final year, you’ll dive into advanced topics and strengthen your practical skills with modules including Artificial Intelligence and Machine Learning, Career Development Learning, Data and Web Development, Formal Languages, Cryptography and Number Theory, Project Analysis and Practice, and a substantial Individual Project. This is where you apply AI and ML techniques, develop web-based data solutions, understand formal specifications, explore cryptography, and complete a major project that connects theory to real-world applications.

Focus Areas

Data Programming
Statistical Modelling
Business Intelligence
Machine Learning
Data Visualisation

These reflect the course’s applied nature, ensuring you graduate with hands-on experience using industry-standard tools and techniques.

Learning Outcomes

Graduates will be able to:

Analyse and interpret complex datasets
Build data-driven solutions using programming and machine learning tools
Design and deploy scalable data systems, including cloud and IoT platforms
Apply modelling techniques to support informed decision-making
Undertake independent, professional, and ethical projects

Professional Alignment

While specific professional accreditations aren’t listed, the program is designed in collaboration with industry experts. It places strong emphasis on professional and ethical issues, preparing you for data-science roles across business, finance, tech, and research.

Reputation & Employability

The course is part of London Met’s School of Computing and Digital Media, within a university recognized by the Teaching Excellence Framework (TEF) for four years from 2023. Though subject-specific rankings aren’t listed, the program prioritizes employability through practical, industry-relevant skills and career development support.

Experiential Learning (Research, Projects, Internships etc.)

You’ll start building practical, hands-on skills from day one. This program immerses you in the most in-demand data science platforms and programming environments—so you’ll be prepared to make a real impact in your career right from the start. Central to your learning is access to powerful digital tools and the university’s blended-learning technology, allowing you to apply theory in real time with the guidance of experienced academics.

Beyond software skills, the course actively supports your career development through placement modules. These are part of your academic credit, not optional extras, ensuring you’re guided into real work environments and receive meaningful feedback on your progress.

Here’s what that looks like in practice:

Technology Tools and Software Environments
You’ll gain hands-on experience with Spark, Kafka, Hadoop, Oracle, SQL Server, Linux, Apache Airflow, RStudio, Python (via Jupyter), Tableau, and D3—tools that are widely used across the data science industry.

Blended Learning Infrastructure
Engage interactively with course materials through the university’s WebLearn platform, and explore e-books and online databases to support your learning and assignments.

Work-Based Learning (Internship) Module
You have the option to replace one module with a credit-bearing internship. The Work-Based Learning team will help you secure a placement, coordinate with employers, and guide your professional development throughout the experience.

Support for Work Placements
The university’s placement initiative offers structured opportunities to work on projects with real businesses, giving you valuable industry experience as part of your studies.

Academic Teaching and Feedback Structure
You’ll participate in a mix of lectures, tutorials, and workshops, with tutors available to support your hands-on learning. Coursework includes group presentations, in-class tests, exams, and practical deliverables such as datasets, code, and reports. Formative and summative feedback will help you refine your skills continuously.

Transitioning into Specifics, Here’s What You’ll Experience:

Software & Tools
Develop fluency in industry-standard tools like Spark, Kafka, Hadoop, Oracle, SQL Server, Linux, Apache Airflow, RStudio, Python (Jupyter), Tableau, and D3.

Digital Learning Platforms
Use the WebLearn environment and access e-books and academic databases to interact with course materials, complete assignments, and receive feedback.

Experiential Work Modules
Engage in an optional, credit-bearing internship, fully supported by the university’s placement team.

Industry-Linked Project Experience
Work on placement-style projects with external organisations, gaining professional exposure and hands-on project experience.

Tutorials, Workshops & Feedback Loops
Attend interactive tutorials and workshops alongside lectures. Receive continuous feedback through group presentations, hands-on assignments, and real-world simulations to hone your skills.

Progression & Future Opportunities

London Metropolitan University’s BSc (Hons) in Data Science equips graduates with practical, industry-ready skills in data programming, analytics, machine learning, and visualisation. Many of our alumni step into roles such as Junior Data Scientist, Data Analyst, Big Data Solution Designer, or IT/Data Consultant. These positions provide a strong entry point into the tech industry, offering competitive starting salaries for entry-level data professionals in London.

Progression & Future Opportunities

University Services
Students benefit from a career-focused curriculum that blends academic learning with hands-on experience. This includes work placements, client projects, and on-campus opportunities that allow you to apply your skills in real-world contexts. If you choose to continue your studies, London Met also offers a generous 20% discount on postgraduate courses.

Employment Prospects & Salary
Graduates leave the program ready to take on roles such as Junior Data Scientist, Associate Data Analyst, Big Data Solution Designer, or IT/Data Consultant. While specific graduate salary figures aren’t publicly listed, the program’s strong focus on industry-relevant tools and practices gives you a competitive advantage in the job market.

Industry Partnerships
The course is shaped with guidance from industry experts, ensuring you learn tools and platforms commonly used in the field. These include Spark, Kafka, Hadoop, Oracle, SQL Server, Python (Jupyter), Tableau, and D3. Exposure to these technologies prepares you for work environments where such skills are in demand.

Accreditation & Long-term Value
While the Data Science BSc does not hold external professional accreditation, it is grounded in rigorous academic foundations from the Mathematics and Applied Computing faculties. The qualification is respected across industries, and alumni consistently highlight the confidence and creativity they gained during their studies. One graduate shared, “With London Met, I discovered I could think outside the box and tackle challenges in innovative ways.”

Graduation Outcomes
This program not only prepares you for immediate industry roles but also opens doors to further study or research. Graduates are well-positioned to pursue postgraduate courses in data analytics, statistics, or related areas, should they wish to advance their expertise further.