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.
What you will study
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.
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.
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