Gain advanced training into the fundamentals of modern machine learning and artificial intelligence with a particular focus on their application to problems across the sciences.
- Year of entry: 2020
- Duration: 1 year full-time
- Mode of study: Full-time
- Entry requirements: 2.1 (or international equivalent) in one of the following areas: physics, mathematics, computer science, chemistry, engineering. A 2.2 (or international equivalent) may be considered if the applicant has relevant work experience or another supporting factor.
- IELTS: 6.5 with at least 6.0 in any element
- UK/EU fees: £8010
- International fees: £24390
- Start date: September
- Course location: University Park
- School/Department: Science, Physics and Astronomy
In the last few years, the development and use of machine learning and artificial intelligence (AI) have revolutionised areas such as computer vision, speech recognition and natural language processing, transforming them from almost intractable problems into useful aspects of our everyday lives.
AI is also fast becoming essential in science for analysing and classifying large sets of data coming from ever more numerous observations and complex experiments. At the same time, the growing interest in the use of machine learning methods has led to new approaches to AI by applying the ideas and techniques of physical sciences which offer distinct and complementary perspectives to those of computer science and software engineering.
The interplay between AI and scientific thinking is central to the spirit of this course. It will provide you with high-quality training, covering the basic theory of machine learning with particular emphasis on the application to real science problems in the form of research projects.
The training in the application of machine learning and AI techniques to problems of scientific relevance helps build the skills that are sought after in research and in industry, enhancing your employability in a rapidly expanding area.
This MSc is aimed at students with an undergraduate degree in one of the following subjects: physics, chemistry, mathematics, computer science or engineering.
- Machine Learning in Science - Part one
- Machine Learning in Science - Part two
- Machine Learning in Science - Project
- Designing Intelligent Agents
- Computer Vision
- Professional Ethics in Computing
- Introduction to Quantum Information Science
- The Physics of Deep Learning
- Neural Computation
In addition, this course offers three alternative strands/pathways which allow you to select different combinations of core and optional modules to meet your interests.
Strand one core modules:
- Machine Learning
- Statistical Machine Learning, 20 credits
Strand two core modules:
- Statistical Foundations
- Fundamentals of Statistics
Strand three core modules:
- Scientific Programming in Python
The above is a sample of the typical modules that we offer but is not intended to be construed and/or relied upon as a definitive list of the modules that will be available in any given year. This course page may be updated over the duration of the course, as modules may change due to developments in the curriculum or in the research interests of staff.
Teaching methods and assessment
This one-year course consists of 180 credits, split into 120 credits of taught modules during the autumn and spring semesters, and a 60-credit research project that is completed in the summer period.
Modules are delivered through lectures and problem classes. There is a wide range of core compulsory modules and optional modules, as well as three alternative strands which allow you to select core and optional modules in different combinations. This allows you to choose modules to fit your undergraduate background and personal interests.
During the summer period, you will concentrate on an independent research project which focuses on the application of machine learning methods, to original scientific problems provided by research groups from across the Faculty of Science. The project involves writing a dissertation and is supervised by a member of the academic staff.
Careers and professional development
Machine learning and artificial intelligence have become central to the economy and society. Graduates with expertise in this area are highly sought after in all sectors that are data-intensive, including IT, finance, consultancy, manufacturing, and large areas of academic and industrial research and development.
Average starting salary and career progression
87.5% of postgraduates from the School of Physics and Astronomy secured work or further study within six months of graduation. The average starting salary was £30,000, with the highest being £31,000.*
* Known destinations of full-time home postgraduates who were available for employment, 2016/17. Salaries are calculated based on the median of those in full-time paid employment within the UK.
Careers support and advice
We offer individual careers support for all postgraduate students whatever your course, mode of study or future career plans.
You can access our Careers and Employability Service during your studies and after you graduate. Expert staff will help you research career options and job vacancies, build your CV or résumé, develop your interview skills and meet employers.
More than 1,500 employers advertise graduate jobs and internships through our online vacancy service. We host regular careers fairs, including specialist fairs for different sectors.
Fees and funding
As a student on this course, we do not anticipate any extra significant costs, alongside your tuition fees and living expenses. You should be able to access most of the books you’ll need through our libraries, though you may wish to purchase your own copies which you would need to factor into your budget.
Scholarships and bursaries
Government loans for masters courses
Masters student loans of up to £10,906 are available for taught and research masters courses. Applicants must ordinarily live in the UK or EU.
International and EU students
Masters scholarships are available for international and EU students from a wide variety of countries and areas of study. You must already have an offer to study at Nottingham to apply. Please note closing dates to ensure you apply for your course with enough time.
This online prospectus has been drafted in advance of the academic year to which it applies. Every effort has been made to ensure that the information is accurate at the time of publishing, but changes (for example to course content) are likely to occur given the interval between publishing and commencement of the course. It is therefore very important to check this website for any updates before you apply for the course where there has been an interval between you reading this website and applying.
About the School
The Faculty of Science undertakes world-class research spanning wide-ranging topics including quantum physics, plant genomics, human imaging, sustainable chemistry, neuroscience, mathematical modellin ... Read More