Program Overview

Introduction to the MSc Artificial Intelligence and Data Analytics Program

The MSc Artificial Intelligence and Data Analytics program at Loughborough University London is designed to equip students with the skills and knowledge required to harness the power of artificial intelligence (AI) and data analytics in a rapidly changing world. This program is ideal for individuals who wish to deepen their understanding of machine learning algorithms, deep learning techniques, and statistical methods for data analysis.

Program Details

• Qualification(s) available: MSc
• Fees: Dependent on start date; see below for details
• Scholarships available: Yes, various scholarships are available
• Entry requirements: 2:2 (50% final year) or equivalent international qualification
• Full-time: 1 year
• Part-time: Up to 4 years
• Location: London
• Start date: October 2025 or October 2026
• Department: Institute for Digital Technologies

Program Structure

The program is structured to provide students with a comprehensive understanding of AI and data analytics, including both theoretical and practical aspects. The curriculum includes:

• Semester 1:
  • Compulsory modules:
    • Programming Fundamentals (15 credits)
    • Principles of Artificial Intelligence and Data Analytics (15 credits)
    • Grand Challenges (15 credits)
  • Optional modules:
    • Design Innovation (15 credits)
    • An Introduction to Sport Analytics (15 credits)
• Semester 2:
  • Compulsory modules:
    • Advanced Big Data Analytics (15 credits)
    • Dissertation (60 credits)
  • Optional modules:
    • Reinforcement Learning (15 credits)
    • Artificial Intelligence and Society: Learning to Live with Machines (15 credits)
    • Internet of Things & applications (15 credits)
    • Cybersecurity and Forensics (15 credits)
    • Advanced Programming and Data Visualisation (15 credits)
    • Collaborative Project (15 credits)
    • Cloud applications and services (15 credits)
    • Game Technologies and Advanced 3D Environments (15 credits)
• Summer:
  • Compulsory module:
    • Dissertation (60 credits)

Assessment and Study

• Assessment: Essays, reports, presentations, projects, and exams
• Study: Lectures, seminars, tutorials, independent study, group work, and practical sessions

Entry Requirements by Country

The entry requirements vary by country. Please refer to the provided table for country-specific requirements.

Fees and Funding

• Fees for the 2025-2026 academic year:
  • UK fee: £13,250 full-time degree per annum
  • International fee: £29,950 full-time degree per annum
• Fees for the 2026-2027 academic year:
  • UK fee: £13,700 full-time degree per annum
  • International fee: £30,900 full-time degree per annum
• Scholarships and bursaries: Available, including the Loughborough University Alumni Bursary, Global Excellence Scholarship, and Excellence Scholarship

Career Prospects

Graduates of this program can pursue a wide range of careers, including:

• Data scientist
• Data engineer
• Technology consultant
• Digital insights manager
• Information systems manager

Related Master's Degrees

• Advanced Computer Science MSc
• Artificial Intelligence MSc
• Cyber Security and Data Analytics MSc
• Digital Innovation Management MSc
• Digital Marketing MSc

Academics

The program is taught by experienced academics, including:

• Dr. Yogachandran Rahulamathavan, Reader in Cybersecurity and Privacy
• Dr. Courtney N. Reed, Lecturer in the Institute of Digital Technologies
• Dr. Varuna De Silva, Programme Director of Artificial Intelligence and Data Analytics
• Sangarapillai Lambotharan, Director of the Institute for Digital Technologies

Conclusion

The MSc Artificial Intelligence and Data Analytics program at Loughborough University London offers a comprehensive education in AI and data analytics, preparing students for a wide range of career opportunities in this rapidly evolving field. With its strong focus on both theoretical and practical aspects, this program is ideal for individuals who wish to deepen their understanding of machine learning algorithms, deep learning techniques, and statistical methods for data analysis.