Course summary
Learn how to research, design and develop machine learning and autonomous systems technologies. You’ll develop the knowledge and skills to solve complex problems. Intelligent and autonomous systems are increasingly important in all areas of our lives, from medicine and space exploration to agriculture and entertainment. Machine learning is at the heart of these systems, including computer vision and robotics. It also underpins the recent developments in data analytics across many fields. Understanding and developing autonomous systems involves a range of skills and knowledge including designing interactive systems with both human and machine elements, and modelling and building systems that can sense and learn. This course will give you the opportunity to develop these skills including the theory of machine learning, artificial intelligence, autonomous systems design and engineering. You’ll also learn about the implications of us interacting with intelligent and autonomous systems more and more. Course highlights
- Study a course designed in collaboration with the Department of Electronic & Electrical Engineering who offer expertise in robotics.
- Learn in a research-led environment from academics with expertise in machine learning, autonomous systems, artificial intelligence and human-computer interaction.
- Work in our bespoke computer lab and take advantage of our strong links with industry, to learn about the latest ideas and technology.
- Be part of a supportive postgraduate community in the Department, with access to a dedicated Personal Tutor who you can go to for academic and non-academic support.
- Gain work experience in industry and increase your employability with an optional placement year.
- Opportunities to take part in extra-curricular activities such as conferences and public engagement events.
- Automated diagnosis of plus disease retinopathy of prematurity using vessel features
- The impact of mindfulness meditation on multisensory transfer learning
- Inner speech classification using convolutional neural networks
Modules
This course lasts 2 years. It starts in September 2023 and ends in 2025. Welcome week starts on 25 September 2023. Occasionally we make changes to our programmes in response to, for example, feedback from students, developments in research and the field of studies, and the requirements of accrediting bodies. You will be advised of any significant changes to the advertised programme, in accordance with our Terms and Conditions. Compulsory course units These compulsory units are currently being studied by our students, or are proposed new units. Year 1 Semester 1 Statistics for data science Machine learning 1 Humans and intelligent machines Robotics software Plus optional unit Semester 2 Research project preparation Autonomous systems navigation, mapping and communications Machine learning 2 Plus optional units Summer You can use the summer to begin your placement or you can do your dissertation first. Placement or Dissertation Year 2 Semester 1 Placement Semester 2 Placement Summer If you choose to do your dissertation in Year 1, you will still be on placement in the summer of Year 2. Dissertation or Placement Optional course units These are examples of optional units currently being studied by our students. Bayesian machine learning Reinforcement learning Artificial intelligence Autonomous systems engineering Placement: Going on placement gives you the opportunity to apply your skills and knowledge during a year working in industry. You’ll be employed full-time in a role to match your future career ambitions, broadening your experience and transferable skills. We have links with companies of all sizes from household names to start-ups. Placement opportunities can't be guaranteed but you will receive tailored support from our specialist team to help you secure a placement.
Assessment method
Coursework Essay Multiple choice examination Online assessment Practical work Thesis Written examination
Entry requirements
British qualifications You should have a first or strong second-class Bachelor’s honours degree or international equivalent. To apply for this course, you should have an undergraduate degree in a course that incorporates a strong element of programming. We may make an offer based on a lower grade if you can provide evidence of your suitability for the degree. If your first language is not English but within the last 2 years you completed your degree in the UK you may be exempt from our English language requirements. English language requirements IELTS: 6.5 overall with no less than 6.0 in all components The Pearson Test of English Academic (PTE Academic): 62 with no less than 59 in any element TOEFL IBT: 90 overall with a minimum 21 in all 4 components You will need to get your English language qualification within 24 months prior to starting your course. If you need to improve your English language skills before starting your studies, you may be able to take a pre-sessional course to reach the required level.
English language requirements
View English language requirements
Fees and funding
Tuition fees
No fee information has been provided for this course
Additional fee information
Provider information
University of Bath
Claverton Down
Bath
BA2 7AY