Overview

• Subject:
  Computing Digital & AI
• Subject-category:
  Data Science
• Duration:
  1 year
• Course Level:
  Postgraduate
• Tution Fees:
  £23650
• Intakes:
  September, 2026,

University Details

The University of Leicester, founded in 1921, is a leading UK university known for its world-class research, innovative teaching, and diverse student community. Committed to academic excellence and global impact, it offers a wide range of undergraduate, postgraduate, and research programs while fostering a supportive and inclusive environment for students from around the world.

English Requirement

IELTS (Academic): Overall score of 6.0 or equivalent is required.

• Some sources mention IELTS 6.5 as the requirement for some data-related courses, but the official MSc AI for Business Intelligence entry page lists 6.0. 

General Requirement

Academic: A UK 2:2 bachelor’s degree (or equivalent international qualification) in a mathematical or quantitatively oriented subject (e.g., Mathematics, Physics). Applicants from computer science backgrounds may be assessed individually.

English (if applicable): If English isn’t your first language, you must meet the university’s English language standard (e.g., IELTS overall ~6.0) — but check the exact required score with admissions

Course Specification

Here’s a very short course specification for the MSc in AI for Business Intelligence at The University of Leicester:

 Core Modules

You’ll study key technical and analytical subjects, such as:

• Fundamentals of Data Science

• Statistics for Data Science

• Computational Intelligence and Software Engineering

• Data Mining and Neural Networks

• AI for Business Intelligence Project (applied research/project work) 

Optional Modules

Choose from options that tailor your expertise, including:

• Mathematical Modelling

• Practical Programming

• Generalised Linear Models

• Introduction to Functional Data Analysis

• International Business

• AI for Space 

 What You’ll Learn

• Apply AI and data analytics to real business challenges

• Use predictive/prescriptive analytics & data mining

• Gain skills in software tools and computational techniques

• Complete a major project based on real datasets 

 Optional Industrial Placement

You can add a 9–11 month industry placement to gain practical experience with real employers, enhancing your career prospects.