Program Overview

Overview of the Artificial Intelligence MSc (Distance Learning) Program

The Artificial Intelligence MSc (Distance Learning) program at the University of Huddersfield is designed to equip students with the knowledge and skills to apply appropriate solutions to real-world problems using a range of AI technologies. This program is aimed at individuals who are not local to the campus or are in employment, providing them with the flexibility to study at their own pace.

Key Information

• Start Dates: The program has multiple start dates throughout the year, including 22 September 2025, 17 November 2025, 16 February 2026, and 18 May 2026.
• Duration: The program is part-time and lasts for 2-3 years.
• Entry Requirements:
  • A BSc or BEng Honours degree (2:2 or above) in Computing or Engineering or a related subject, or an equivalent professional qualification.
  • For applicants who received their degree more than 10 years ago, evidence is required to demonstrate current knowledge in the subject area, such as reference letters, training certificates, or significant relevant work experience.
  • Other qualifications and/or experience that demonstrate appropriate knowledge and skills at an Honours degree level.
  • If the first language is not English, students must meet the minimum requirements of an English Language qualification, with a minimum IELTS score of 6.0 overall and no element lower than 5.5, or equivalent.

Course Detail

The program covers a range of areas, including machine learning, data mining, robotics, knowledge graphs, and autonomous systems. The course is fully accredited by the British Computer Society (BCS), the Chartered Institute for IT, and upon completion, students will have partially fulfilled the academic requirements for registration as a Chartered IT Professional.

Modules

• Machine Learning: This module provides a fundamental understanding of machine learning techniques, including data-driven approaches and specific techniques such as deep learning.
• Data Mining: This module explores different data mining techniques and the use of appropriate data-mining tools to evaluate the quality of discovered knowledge.
• Robotics: This module examines the integration of mechanical devices, sensors, and intelligent computerized robotic agents, covering essential techniques for the design and development of robotic-based systems.
• Knowledge Representation and Reasoning: This module introduces principles, languages, and algorithms for representing information about the world in a form that computer systems can manipulate and utilize to solve complex tasks.
• Autonomous and Autonomic Intelligent Systems: This module covers the background and requirements for intelligent systems autonomy, including technical challenges, ethical and legal issues, and human factors implications.
• Case Studies in Data Analytics and Artificial Intelligence: This module enables students to appreciate the historical, current, and future application areas of Artificial Intelligence and Data Analytics.
• Effective Research and Professional Practice: This module provides skills key to becoming a successful computing researcher or practitioner, including the nature of research, the scientific method, research methods, and literature review.
• Artificial Intelligence Planning: This module recaps the history of automated planning and focuses on the kinds of assumptions, algorithms, heuristics, and representation languages used to create generative planning algorithms.
• Individual Project: This module allows students to work independently on a project related to a self-selected problem, with the option to undertake an in-company project with an external client.

Teaching Excellence

The University of Huddersfield is recognized for its teaching excellence, with staff who are members of the University's Centre for Autonomous and Intelligent Systems and are at the forefront of impactful research. The course follows a flipped learning approach, with each module including recorded lecture content and a series of asynchronous learning activities.

Career Support

The University provides professional help, support, and guidance through its Careers and Employability Service, including industry-supported workshops, careers fairs, and one-to-one guidance sessions. The service helps students focus on life after graduation to ensure that their hard work pays off and they achieve their ambitions.

Fees and Finance

• Tuition Fees: For the academic year 2025/26, the total fee for UK and international students on this course is £9,900.
• Corporate Discounts: Employers looking to enroll a number of learners may be eligible for a corporate discount.

Accreditations and Professional Links

The course is accredited by the British Computer Society (BCS), the Chartered Institute for IT, providing an indicator of quality to students and potential employers. Accreditation also gives students a potential advantage when looking for a job, as some employers may ask for graduates with accredited degrees.

Student Support

The University offers support networks and services to help students get ahead in their studies, including the Distance Learning Unit Team, which provides specialist staff committed to ensuring that online teaching and learning material is accessible to all. The University also recommends and provides training on assistive technologies and software to support a range of learning styles and additional needs.

Research Excellence

The University of Huddersfield is in the top 50 UK universities for Research Power, with three-quarters of all its research being world-leading and internationally excellent. The University's researchers carry out work that makes a real difference to people's lives, and the institution is a member of Yorkshire Universities.

Conclusion

The Artificial Intelligence MSc (Distance Learning) program at the University of Huddersfield offers students a comprehensive education in AI technologies, with a focus on practical skills and theoretical knowledge. With its flexible part-time structure, the program is ideal for individuals who want to advance their careers in AI without having to attend campus full-time. The University's commitment to teaching excellence, career support, and research excellence makes it an attractive choice for students looking to pursue a master's degree in AI.