Artificial Intelligence (Taught)

Please check the Sheffield Hallam University website for the latest information.

Course summary

• Study modern AI practices, theories, techniques and ethical considerations.

• Develop your problem-solving skills by applying AI methods.

• Gain in-depth understanding by exploring rigorous development processes.

• Cultivate a substantial portfolio of commercial-quality work.

On this course you’ll learn techniques relevant to the field of AI, from machine learning and to natural language processing. You’ll consider real-world challenges while developing your problem-solving and professional skills – plus a portfolio that enhances your employability in the dynamic field of AI, as well as other related industries.

How you learn
At Sheffield Hallam, all our courses are designed to engage you with the world and challenge you to think in new ways. You’ll get to collaborate with others, and you’ll be taught in a supportive environment where you can thrive.

This course emphasises hands-on learning in AI and machine learning, covering key areas like neural networks, robotics, natural language processing and computer vision.

You’ll prepare for real-world challenges through practical projects and collaborations with industry partners. The course also focuses on ethical considerations, security, privacy, and AI bias, encouraging a responsible approach to AI. Our expert staff help you gain both theoretical knowledge and practical skills, enhancing your employability.

You learn through:

• Lectures

• Tutorials and seminars

• Regular feedback

• Laboratory sessions

• Real-world problems

• Practical activity-based sessions

• Group and individual project work

• Supervisor support and guidance

• Acting as mentors for new students

• Self-directed study

Key themes
You’ll explore technical concepts across key areas of AI, including machine learning foundations, neural networks, cognitive systems for robotic logic and computer vision techniques. When combined, these lead into early course projects such as simulating a self-driving robot and evaluating its success.

You’ll then progress onto larger projects with industry clients that solve real-world problems. During those projects, you’ll have regular scrum meetings with academics and clients that identify narratives, learning needs and action plans to progress. You could find yourself working on a recommendation system for a retail company, or training robot football players to win the robot football world cup.

Ultimately you’ll engage in and with AI research, enhancing your learning and leading into your individual dissertation project. This is your opportunity to tailor your own piece of work in the discipline – as wide ranging as a computer-game-playing robot to screening skin conditions – with regular support from your supervisor.

Applied learning
Work placements
This course has a work experience route that offers a placement in industry of up to 12 months. For further information, please see MSc Artificial Intelligence (Work Experience).

Important notice: The structure of this course is periodically reviewed and enhanced to provide the best possible learning experience for our students and ensure ongoing compliance with any professional, statutory and regulatory body standards. Module structure, content, delivery and assessment may change, but we expect the focus of the course and the learning outcomes to remain as described above. Following any changes, updated module information will be published on this page.

Modules studied may differ depending on when you start your course.

Final year
Compulsory modules
Advanced Robotics And Artificial Intelligence
Ai Development Project
Artificial Intelligence Seminar Series
Computing Research Project
Deep Neural Networks And Learning Systems
Research Skills For Computing

Coursework.