Programme Type:

Course Overview

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 provide 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.

Entry Requirement 

This course is aimed at graduates with a minimum of 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.

Fees

Full-time UK:  £9000

Full-time International:  £14500 

Part-time UK:  £1000 per 20 credits


This information was accurate on : 03/05/2021
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