City, University of London

City, University of London

Artificial Intelligence

This programme is for recent graduates, and those already working, with a strong grounding in mathematics, good imagination and creativity and an appreciation for data. The MSc also requires programming experience, preferably, but not limited to, Java, C++ or Python. You will need to have a degree in mathematics, engineering or computer science, or a degree in natural sciences, including psychology. You must also be able to envisage and create models and algorithms so you can work with data to find out what it means and says. Our focus is on the most commercially applicable form of AI, known as Deep Learning - developing adaptable artificial neural networks (ANNs) that replicate how the brain works. You also explore the wider issues of ethics, accountability and trust that surround AI and how "Explainable AI" is used to interpret the functioning of complex ANNs. The course is hands-on, using the new world-class City AI Lab, which provides the latest computers, tools and technologies, and the GPU power needed for Deep Learning. Here, as part of your project work and in preparation for employment or future research, students work on how to apply AI to real-world problems, with active researchers in AI.

Entry requirements

MSc: The programme is designed for those who have completed a first (or upper second class) degree in science and technology subjects including computer science, mathematics, physics, engineering, psychology or biology. You must have competence in at least one object-oriented programming language (preferably Python, but Java or C++ are also adequate) and mathematics (linear algebra and calculus, in particular).

Course modules

Core Modules: - Introduction to Artificial - Programming and Mathematics for Artificial Intelligence (15 credits) - Computational Cognitive Systems (15 credits) - Explainable Artificial Intelligence (15 credits) - Deep Learning 1: Classification (15 credits) - Deep Learning 2: Prediction (15 credits) - Deep Learning 3: Optimization (15 credits) - Agents and Multi-Agent Systems (15 credits) - Individual Project (60 credits)

Assessment methods

This practical MSc is assessed solely on coursework, one assessment per module, which includes an oral presentation of your work. This could be through theoretical questions such as short essays, or practical assignments where you analyse and give examples of AI methods and techniques. To reflect the real-life practice of Artificial Intelligence your work is often in teams. We may ask for separate oral presentations when assessing team assignments so that each member can demonstrate their contribution. The individual project is your chance to solve a real problem - for instance collecting and processing real data, designing and implementing AI systems, and applying and evaluating them. Under the supervision of academic staff, and working with industrial partners where appropriate, your task is substantial - to develop and resolve an original research-related topic. You can also carry out your individual project as a 6-month internship.

Qualifications

Qualification Study mode Start month Fee Course duration
MSc Full-time September 2019 9,500 per Whole course (England) 1 Years
MSc Full-time September 2019 9,500 per Whole course (EU) 1 Years
MSc Full-time September 2019 20,000 per Whole course (International) 1 Years
MSc Full-time September 2019 9,500 per Whole course (Northern Ireland) 1 Years
MSc Full-time September 2019 9,500 per Whole course (Wales) 1 Years
MSc Full-time September 2019 9,500 per Whole course (Scotland) 1 Years

Campus details

Campus name Town Postcode Region Main campus Campus Partner
Northampton Square EC1V 0HB London

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