MSc Artificial Intelligence (Machine Learning)

About this course

A very topical course, combining theory and practical aspects of machine learning with a view to forming capable professionals for the jobs market in this field.

• Embark on this newly developed course on a topic of great recent and predicted growth
• Explore the theory of machine learning and practical applications
• Benefit from studying both the practical focus and real industrial applications - this is one of a small number of such courses available
• Learn from academics with substantial experience in machine learning and industrial collaboration

Machine Learning is the scientific study of the ways in which computer systems can be programmed to perform a specific task without using explicit instructions, relying on patterns and inference instead through algorithms and statistical models.

This course is unique in combining theoretical and practical aspects of Machine Learning that will prepare graduates for a career in Industry or Academia. Modules include both aspects throughout the programme and prepare graduates for a variety of roles in Machine Learning development and deployment.

• an undergraduate degree in a cognate subject area

or

• A Honours degree in a non-cognate subject area when supplemented by relevant skills and / or experience

or

• Degree equivalent professional qualifications, e.g. BCS Professional Graduate Diploma in IT

or

• A HND plus a minimum of three years of relevant professional experience

Employability

Further your career prospects

LJMU has an excellent employability record with 96% (HESA 2018) of our postgraduates in work or further study six months after graduation. Our applied learning techniques and strong industry connections ensure our students are fully prepared for the workplace on graduation and understand how to apply their knowledge in a real world context.

As a machine learning graduate, you can expect to be responsible for creating software, algorithms and mechanisms that support intelligent systems, that can learn and develop themselves as they operate. Self-driving cars, pattern recognising predictive systems, for instance, are examples of such systems. Machine Learning medical systems that can recognise patterns to predict health outcomes are becoming increasingly relevant for medical prediction and diagnosis.

You will provide computers with the automatic ability to learn, fine tune and improve performance with their own experience.

In addition, there are huge opportunities in research, both academic and in industry, developing new algorithms, systems and conducting experiments on intelligent systems.