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BSc (Hons) Data Science

  • Undergraduate
  • London
BSc (Hons) Data Science
London Metropolitan University

Course Overview

Intake

N/A

Duration

3 years

Course Description

The Data Science BSc degree at the institution offers a comprehensive introduction to the most important areas of the discipline, including data programming, statistical modelling, business intelligence, machine learning and data visualisation. Developed with input from industry experts, this course covers the essential skills and competencies required to excel in this fascinating field. By the end of the degree, students will be prepared for rewarding roles in the data science and big data industries, as well as the many sectors that increasingly require data scientists. Designed by academics from both mathematics and applied computing backgrounds, the course fosters learning development using a range of tools and big data platforms. Students will gain proficiency in technologies such as Spark, Kafka, Hadoop, Oracle, SQL Server, Linux, Python and Tableau. The course is available for full-time study over three years, with part-time options also available. Throughout the programme, students are encouraged to apply maths, statistics and science practice to solve domain-specific problems and build scalable data products.

Tuition Fee Details

The tuition fee for UK home students is £9,790 per year for full-time study. Tuition fees for subsequent years may be subject to inflationary increases by the UK government. The university reserves the right to increase the tuition fees in line with changes to legislation, regulation and any government guidance or decisions. More information on the latest fee can be found on the institution website.

Course Structure

Data Analysis

15 Credits

Financial Mathematics

15 Credits

Fundamentals of Computing

15 Credits

Introduction to Information Systems

15 Credits

Logic and Mathematical Techniques

30 Credits

Programming

30 Credits

Frequently Asked Questions

Graduates are prepared for roles such as data analyst, data scientist, data engineer, and business intelligence developer, with opportunities in sectors ranging from technology to finance.