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MSc Data Science and Artificial Intelligence (Conversion)

  • DeadlineStudy Details:

    30 months (part-time and online)

Course Description

The Data Science and Artificial Intelligence MSc programme has been designed to provide students with a non-computer science first degree with the necessary technical knowledge and skills required to take up rewarding careers within the data science and artificial intelligence (AI) industry, including interdisciplinary career opportunities.

The programme will allow students to build on their existing undergraduate degrees, and upskill their portfolio of abilities, in the context of current thinking in the domain of data science and AI. More specifically the programme will provide students with a comprehensive insight into the modern data analytics landscape with a focus on data science and AI.

On completion of the programme, you will have gained a systematic insight into the current state of the art, and current thinking, within the remit of data science and artificial intelligence in particular, and computer science in general. The programme will complement your first-degree knowledge with a deep and systematic insight into the domain of data science and artificial intelligence.

During your studies, you will develop your ability to work independently, and with others, to research, design, implement and execute creative data science and artificial intelligence solutions to practical and commercial problems, and to subject your work and that of others to critical analysis and evaluation.

You will also have an opportunity to create a professional development plan and, throughout the course of the programme, build an e-portfolio that exhibits your understanding of computer science and the practical application of computer science technology.

Entry Requirements

Applicants should possess either:

  • A minimum of a 2:2 class degree in a suitable technical subject other than computer science or IT, equivalent to a UK bachelor’s degree, coupled with two years’ experience in employment; or
  • Professional work experience and/or other prior qualifications, which will be considered on a case-by-case basis.

All applicants must have reached a minimum required standard of English language and are required to provide evidence of this. Successful applicants from outside the UK must have an International English Language Testing System (IELTS) score of 6.5 overall or equivalent.

Fees

Full tuition fee – £15,300 (2022/2023 academic year)

Full tuition fee – £16,065 (2023/2024 academic year)

Programme Funding

A UK Scholarship of 10% is available for students residing in the United Kingdom. This scholarship is available for our intakes in the 2023/24 academic year for all full master’s awards.

Student Destinations

Successful completion of the programme will allow you to take up careers in the growing area of data science and artificial intelligence, or in many other computer science settings, including interdisciplinary roles related to your undergraduate degree. The skills you develop will be of use in a wide range of industries including healthcare, government agencies and technology. Potential job titles are varied, and include examples such as data analyst, data scientist, database manager, machine learning practitioner and IT consultant.

Module Details

The Data Science and Artificial Intelligence MSc consists of the following taught modules and a final dissertation project. There is a brief break scheduled between modules to allow students to refresh themselves and reflect on what they have learned.

Shorter postgraduate diploma (120 credits) and postgraduate certificate (60 credits) awards are also available in this subject.

  • Global Trends in Computer Science (15 credits)
  • Mathematics and Statistics for Data Science (15 credits)
  • Software Development in Practice (15 credits)
  • Databases and Information Systems (15 credits)
  • 3 elective modules from (3×15 credits):
    • Reasoning and Intelligent Systems
    • Machine Learning in Practice
    • Multi-Agent Systems
    • Robotics
    • Deep Learning
  • Natural Language Processing and Understanding
  • Deep Learning (15 credits)
  • Research Methods in Computer Science (15 credits)
  • Computer Science Capstone Project (60 credits)

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