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BSc (Hons) AI and Data Science UCAS: G5AI

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Manchester Metropolitan University

Course Level
Undergraduate
Course Subject
Data Science

Course Description

 

Overview

Extracting actionable insights from complex datasets and deploying autonomous intelligent systems are vital capabilities driving global technological transformation. The BSc (Hons) AI and Data Science at Manchester Metropolitan University delivers a scientific and practical education designed to equip students with core expertise across automated reasoning, statistical modeling, and computing architectures. Situated within Manchester’s prominent technology sector, the program is taught in the £115 million Dalton Building, featuring high-specification computing laboratories, a usability laboratory, and a dedicated mathematics and computing studio. The curriculum balances foundational programming, software engineering, algorithms, and data engineering with modern deep learning applications and data governance principles. Affiliated educationally with professional bodies such as the British Computer Society and the Chartered Institute of Information Security, the degree offers collaborative group development projects, live industry challenges, and an optional four-year placement pathway. This program is ideally suited for logically minded, analytical individuals who wish to build algorithmic models, extract value from complex data streams, and launch technical careers across artificial intelligence, quantitative analysis, and technology consultancy.

What You'll Learn

  • Fundamental programming paradigms, software development practices, object-oriented design, and code optimization

  • Core concepts in machine learning, intelligent systems engineering, predictive modeling, and deep learning architectures

  • Mathematical foundations for computing, including statistical modeling, linear algebra, discrete mathematics, and probability theory

  • Principles of data engineering, relational database design, SQL queries, and large-scale data storage systems

  • Algorithms and data structures, computational complexity, and performance evaluation techniques

  • Data science methodologies, exploratory data analysis, pattern recognition, and quantitative data visualization

  • Ethical implications of technology, AI regulations, responsible software design, and data governance frameworks

  • Specialized artificial intelligence applications, including natural language processing, computer vision, and autonomous agent design

  • Major final-year individual capstone software development or empirical research project addressing a complex data science problem

Learning Outcomes

Graduates will possess an in-depth understanding of machine learning algorithms, computational statistical models, database engineering architectures, and technical AI governance standards. They will demonstrate the capability to design custom data processing pipelines, construct predictive machine learning models, analyze complex datasets, and evaluate the ethical and social impacts of autonomous technologies. Students build strong practical competencies in multi-paradigm programming, data manipulation software, statistical analysis, and neural network training through hands-on laboratory workshops, collaborative software projects, and industry-oriented assignments. Furthermore, scholars master the ability to communicate technical data insights clearly, document system architectures, and present data-driven solutions to both technical specialists and executive non-expert stakeholders. Through research-led instruction, modern computing infrastructure, and close links to Manchester’s digital sector, graduates cultivate the technical precision, logical agility, and strategic problem-solving skills required to excel as machine learning engineers, data scientists, AI developers, data architects, business intelligence analysts, or postgraduate researchers.

 

Requirements

Kuwait: High School / Shahadat Al-Thanawiya Al-A'ama (General Secondary Education Certificate) with a minimum of 75% and 70% in Maths.
UKVI IELTS (Academic) 6.0 overall with no band below 5.5 (or approved SELT equivalent)
Minimum overall average of 50% (120 academic credits) in the Foundation Programme required to progress to Year 1 of the Bachelor's degree
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£21500.00
Tuition fee
Apply by October 16, 2026
Start dates
Sep 2027, Sep 2028
Duration
3 Years
Campus
Main Campus
Mode of study
Full Time
Fees and deadlines depend on the selected options.
Fees and currency conversion are approximate.
⏳ Offer response
1-2 Weeks
📄 Backlogs accepted
This course accepts backlogs