MSc Artificial Intelligence (Machine Learning)

at Bucks New University

Core modules
 

• Research Methods
• Project Dissertation
• Deep Learning Concepts and Techniques
• Accelerated Machine Learning
• Advanced Topics in Deep Learning
• Enterprise Machine Learning
• Foundations of Machine Learning
   

You will need:

• an undergraduate degree in a cognate subject area

or

• an undergraduate 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 relevant professional experience
   

Additional information

• IELTS score of 6.0 (5.5 each component)

• Non-standard applications are welcome. Admission will be at the discretion of the Programme Leader. Applicants may be required to submit a CV and references. Please contact the Admissions Team for further information

Tuition fees
 

• Home (full-time, per year):£8,500
• International (full-time, per year):£16,600

LJMU has an excellent employability record with 96% (Graduate Outcomes, 2018/19) of our postgraduates in work or further study 15 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.