MSc Artificial Intelligence

USW’s new MSc Artificial Intelligence is a conversion course aimed at graduates who would like to broaden their existing knowledge and open up a new career path. 

Artificial intelligence aims to automate the completion of highly complex tasks and increase productivity, as well as use data to get a competitive edge or increase market share.

As a result, artificial intelligence has broad application in a variety of industries from mobile communications and computer security to healthcare, manufacturing, marketing and financial services and is a key growth area for jobs.

The AI masters will develop technical training in the fundamentals of artificial intelligence including machine learning techniques; autonomous systems; deep learning and computational intelligence, as well as core skills in data analysis, project management and research.

You will learn to think logically and creatively, and to communicate effectively, both orally and in writing, for technical and lay audiences. Applications from engineering, IT, science, mathematics or business graduates in particular are welcomed. All entrants must have strong numeracy and IT skills. 

Study Mode
2019
Duration Start Date Campus Campus Code
Full-time 1 Year September Treforest A
Part-time 2 Years September Treforest A

Modules include work based on research by the Computer Science and Artificial Intelligence Paradigms (CSAIP) research group.

  • Project Management and Research Methodology - 20 credits
    Project Management and Research Methodology provides students with the opportunity to plan a project using appropriate methods, techniques and tools, taking into account relevant risks and ethical issues, and undertake a literature review and other development activities to improve their understanding of the situation and/or produce organisational change.

  • Principles of Computing - 20 credits
    Principles of Computing provides students with the opportunity to demonstrate a comprehensive understanding of current developments in computer technology, programming and database systems and to apply appropriate practices, tools and techniques to produce a solution to a problem where there are many interacting factors.

  • Applied Statistics for Data Science - 20 credits
    Applied Statistics for Data Science provides students with the opportunity to understand the concepts and theory of statistical analysis, and explain the wider context of their value in Data Science as well as determine and use statistical techniques to assess practical situations and interpret real-world complex data.

  • Knowledge-Based Systems - 20 credits
    Knowledge-Based Systems provides students with the opportunity to gain a broad introduction to applicable artificial intelligence alongside practical skills designing and developing knowledge-based systems used to support human decision-making, learning and action, and appreciate their implications to society.

  • Machine Learning and Autonomous Systems - 20 credits
    Machine Learning and Autonomous Systems provides students with the opportunity to build a foundational understanding of machine learning and autonomous systems, approaches to their design and development, areas of application, available tools and their implications to society.

  • Deep Learning - 20 credits
    Deep Learning provides students with the opportunity to build on their knowledge of machine learning and explore the field of deep learning, areas of their application, approaches to the design and development of solutions to problems and available tools.

  • MSc Project - 60 credits

Teaching

This AI masters is aimed at graduates with engineering, science, IT, mathematics or business backgrounds who have strong numeracy and IT skills.

It is delivered in four major blocks to offer an intensive but focused learning pattern. Full-time students will typically spend 12 hours in classes and 24 hours outside of classes each week.

If you choose to study part-time, this is reduced to around six hours each week. You will study through lectures, tutorials, practical sessions, seminars and projects.

You will need to spend a significant amount of time working independently, reading and preparing for assessments. 

You will also work on a significant research project of your own choice, where strong independent thinking, critical analysis and project management skills will be important.

Assessment

Assessment is primarily by coursework (94%), varying from a research-style paper or essay to practical assignments.

You will also work on a significant research project of your own choice, where strong independent thinking, critical analysis and project management skills will be important.

Placements

Through the Erasmus scheme, students could have the opportunity to attend summer schools in advanced computer vision and machine learning with our partners in TEI of Crete, University of Patras, University of Burgundy, Cyprus University of Technology, Polytechnic Institute of Porto and the University of Salento.

Facilities

Practice is so important in gaining understanding of complex machine learning techniques, which is why we have a range of high specification computer laboratories including workrooms dedicated to our masters’ students.

These facilitate a learning environment where you can work individually or in groups and as they are located close to the staff offices.

Our facilities are at the cutting edge of computer development, meaning you’ll use the latest technologies in high-spec labs.

You’ll also find dedicated spaces on campus for computing students, including Windows, Apple Mac, Linux and Networking suites, all with the latest software.

Lecturers

This course is aimed at graduates with a minimum 2:2 Honours degree or equivalent who would like to broaden their existing knowledge and open up a new career path.

Applications from engineering, IT, science, mathematics or business graduates in particular are welcomed.

All entrants must have strong numeracy and IT skills.

The course welcomes international applicants and requires an English level of IELTS 6.0 with a minimum of 5.5 in each component or equivalent.

 

Full-time fees are per year. Part-time fees are per 20 credits. Once enrolled, the fee will remain at the same rate throughout the duration of your study on this course.

August 2019 – July 2020 Fees: USW will be offering a package of financial support for postgraduate study and this will be announced shortly.

August 2019 - July 2020 Fees


  • Full-time UK and EU:  £9000

  • Full-time International:  £13400 

  • Part-time UK and EU:  £1000 per 20 credits

Additional Costs

Students have access to a wide range of resources including textbooks, publications, and computers in the University’s library and via online resources. In most cases they are more than sufficient to complete a course of study. Where there are additional costs, either obligatory or optional, these are detailed below. Of course students may choose to purchase their own additional personal resources/tools over and above those listed to support their studies at their own expense. All stationery and printing costs are at a student’s own expense.

Apply directly to the University for the MSc AI course.

Admissions statement 

Graduates with an MSc Artificial Intelligence will be able to apply for jobs in artificial intelligence, competitive intelligence, business intelligence, threat intelligence, cyber intelligence, computational intelligence, customer intelligence and marketing intelligence.

Example job titles include machine learning engineer, artificial intelligence engineer and business intelligence data engineer.

Many of our computing graduates commence doctoral research here at the University, and there are PhD research opportunities in artificial intelligence within the school and beyond.