Data Science (including foundation year) - BSc (Hons)

With modules covering mathematics, programming, an introduction to cyber security and more, this foundation year will put you well on the way to a career in this fascinating field.

Course details

Looking to pursue a career in Data Science, but don’t yet have the qualifications or experience to begin our three-year course? Our Data Science (including foundation year) BSc route is the perfect opportunity for you to meet the necessary entry requirements to join our traditional three-year degree course. Completing the foundation year will see you join the students from our Data Science BSc, meaning you’ll graduate with the same title and award as those who studied the three-year course.
  • Mode of study: 2 -3 days campus
  • Intake: September , January
  • Course length: 3-4 years
  • Course fee: £9,250 per year
  • Location: London

London Metropolitan University

Course overview

Designed with your interests and future in mind, you’ll acquire practical data science skills, often developed by external organizations, which will prepare you for employment. Throughout your four years studying on the course you’ll also be trained in the use of up-to-date software tools and environments currently used by the industry sector. This includes tools such as Spark, Kafka, Hadoop, Oracle, SQL Server, Linux, Apache Airflow, RStudio, Python – Jupyter, Tableau, and D3 technology. You will also find opportunities to learn from real-life case scenarios.


Entry requirements

at least one A level (or a minimum of 32 UCAS points from an equivalent Level 3 qualification, eg BTEC Subsidiary/National/BTEC Extended Diploma)

English Language and Mathematics GCSEs at grade C/4 or above (or equivalent, eg Functional Skills at Level 2)

What the students say

The highlight of my time at London Met so far has been using the resources made available by the University, especially the careers department, along with the skills obtained on my degree to successfully secure an intern finance position in my first year.


The modules listed below are for the academic year 2022/23 and represent the course modules at this time. Modules and module details (including, but not limited to, location and time) are subject to change over time.

  • Cyber Security Fundamentals (core, 30 credits)
  • Introduction to Robotics and Internet of Things (core, 30 credits)
  • Mathematics (core, 30 credits)
  • Programming (core, 30 credits)
  • Data Analysis and Financial Mathematics (core, 30 credits)
  • Fundamentals of Computing (core, 15 credits)
  • Introduction to Information Systems (core, 15 credits)
  • Logic and Mathematical Techniques (core, 30 credits)
  • Programming (core, 30 credits)
  • Data Analytics (core, 15 credits)
  • Data Engineering (core, 15 credits)
  • Databases (core, 15 credits)
  • Professional Issues, Ethics and Computer Law (core, 15 credits)
  • Programming with Data (core, 15 credits)
  • Smart Data Discovery (core, 15 credits)
  • Statistical Methods and Modelling Markets (core, 30 credits)
  • Artificial Intelligence and Machine Learning (core, 15 credits)
  • Big Data and Visualisation (core, 15 credits)
  • Project (core, 30 credits)
  • Academic Independent Study (option, 15 credits)
  • Advanced Database Systems Development (option, 30 credits)
  • Artificial Intelligence (option, 15 credits)
  • Cryptography and Number Theory (option, 15 credits)
  • Ethical Hacking (option, 15 credits)
  • Financial Modelling and Forecasting (option, 30 credits)
  • Formal Specification & Software Implementation (option, 30 credits)
  • Work Related Learning II (option, 15 credits)