the United Kingdom
Northeastern University London| The award | How you will study | Study duration | Course start | Domestic course fees | International course fees |
|---|---|---|---|---|---|
| MSc | Full-time | find out | find out | find out | find out |
MSc Responsible Artificial Intelligence
The field of Artificial Intelligence (AI) is expanding exponentially as a result of technological advances in software, hardware, and algorithmic techniques. As a result, there is an emerging need for these technologies to be further informed by ethical and political considerations.
In a world where AI prevails, organisations will increasingly require graduates who combine expertise in the development and implementation of machine learning applications with a keen understanding of societal and ethical considerations, and the ability to communicate.
The MSc Responsible Artificial Intelligence addresses this need for interdisciplinary engagement by teaching students the computational and programming techniques that underpin contemporary AI, while providing a philosophical grounding in the field.
Award:MSc Responsible Artificial Intelligence
Location:St Katharine Docks, London
Study mode:Full-time or part-time
Duration:One year (FT) or two years (PT)
Start date:6th September 2023 (see academic calendar)
Annual tuition fees:Home: £11,000 (FT) /£5,500 (PT)
International: £14,000 (FT) / £7,000 (PT)
Northeastern University London Alumni Fees Discount: 20%
Funding:Postgraduate loan available
Programme Specifications:Click here
Why choose our MSc Responsible AI?
Introduction
The option to study philosophical issues of AI whilst pursuing a Masters level computing degree is a unique offering in the UK, allowing students the opportunity to delve on the technical as well as the societal impact of data processing and, in particular, machine learning applications.
The programme allows students to progressively develop their understanding of the techniques of data science, machine learning, and natural language processing, alongside key concepts and methods of computer science, while honing their programming skills in Python and Java; and, at the same time, refine their thinking and communication skills, through humanities courses devoted to a consideration of key practical and theoretical issues, arising in connection with AI.
Structure
The MSc Responsible Artificial Intelligence consists of eight taught courses, six courses (90 credits) in Computer and Data Science and two courses (30 credits) in the Humanities, plus an individual software development project (60 credits).
The six computing courses teach students the theory and application of computer and data science, especially in relation to Artificial Intelligence (AI). They are taught in pairs, one per term. In each pair, one course always complements the teaching of its counterpart. In Michaelmas term, students learn the basics of programming (e.g. control flow statements and data collections), alongside the fundamentals of computing (e.g. logic operators, algorithm complexity and data structures). In Hilary, students learn how to ingest and transform data (e.g. numerical arrays, images or text), alongside how to design and structure programs. Finally, in Trinity students learn how to develop machine learning applications at breadth and depth. We choose Natural Language Processing to study depth because it has a profound technical and societal impact nowadays and it is pertinent to humanics.
The two humanities courses teach students to think carefully and communicate clearly about philosophical (ethical and other) issues arising in relation to computing, data usage, AI, and other emerging technologies.
The individual project offers an opportunity to students to pursue impactful interdisciplinary projects on an agreed topic of their choice in digital humanities or computational social sciences within the University and with its partners. It runs throughout the year so that students have ample time to focus their independent learning with the right guidance by their supervisor(s). Students will gain experience interacting with non-technical audiences to gather problem specifications and explain solutions.
Teaching & learning
The MSc Responsible Artificial Intelligence will be delivered through a mixture of lectures, seminars, lab-based tutorials and office hours.
Students who are enrolled full-time should anticipate devoting approximately 35-40 hours per week to their studies for the duration of their degree. In Michaelmas and Hilary terms, this will include approximately six to seven formal contact hours per week, with the remainder consisting of structured independent study.
Part-time study
The Masters programme can be taken part-time over two years. Part-time students attend the same classes as their full-time colleagues, taking 50% of the course load each academic year. The classes are not run separately in the evening for part-time students.
While we try to make the part-time study as flexible as possible, our Master's programmes are demanding and we advise students that, if they intend to work alongside the course, their work should be flexible.
Timetables
Timetables are usually made available to students during Freshers' Week. Teaching can be scheduled to take place during any day of the week. However, when possible, Wednesday afternoons are usually reserved for sports and cultural activities.
Career Opportunities
Artificial Intelligence and, more specifically, the application of machine learning techniques to big data sets is becoming increasingly prevalent in society. There is an increasing need in the tech and public sector for graduates who can not only develop machine learning applications well, but who can also understand the issues that arise in relation to such applications; and who can communicate technical and societal issues clearly.
In addition to their degree, students of the MSc Responsible Artificial Intelligence have access to personalized guidance to help clarify and create practical plans to achieve career aspirations. In addition, they enjoy opportunities to network with our partner-employers in the technology and public sector, while studying just minutes from both London's Central Business District and East London Tech City.
Contact Northeastern University London to find course entry requirements.
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