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  1. Artificial Intelligence
    1. 2019
Courses

MSc Artificial Intelligence

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Entry Year:
Artificial Intelligence (AI) is transforming society and is sought after by industry, government and academia. City's practical MSc trains you in cutting-edge nature-inspired Artificial Intelligence in London.

Key Information

Start date

September 2019

Academic year dates

Duration

12 months (15 months with option of three month internship)

UK/EU

Full-time: £9,500

Non-EU

Full-time: £20,000

Campus

Northampton Square

Who is it for?

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.

Objectives

What is Artificial Intelligence? AI seeks to simulate intelligence and apply the resulting algorithms to solve real-life problems. AI professionals are in huge demand in fields including health, finance, transport and energy, as well as in neuroscience.

On City's MSc in Artificial Intelligence, you learn advanced AI technology and how to apply it to problems in data classification, prediction and forecasting, optimization, as well as in computational modelling of learning and behaviour.

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.

Requirements and how to apply

Entry requirements

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).

English requirements

For overseas students whose first language is not English, the following qualification is required:

  • IELTS: 6.5 (minimum of 6.0 in all four components)

Due to changes in the UKVI 's list of SELT s we are no longer able to accept TOEFL as evidence of English language for students who require a CAS as of April 2014.

English language programmes

Don't meet the English language requirements? INTO City, University of London offers English language programmes to help prepare you for study at university. These intensive and flexible courses are designed to improve your English ability for entry to degree courses.

Visa requirements

If you are not from the European Economic Area / Switzerland and you are coming to study in the UK, you may need to apply for a visa or entry clearance to come to the UK to study.

The way that you apply may vary depending on the length of your course. There are different rules for:

  • Students on courses of more than six months
  • Students on courses of less than six months
  • Students on a pre-sessional English language course.

For more information see our main Visa page.

How to apply

Thank you for having decided to apply to study a postgraduate course at the School of Mathematics, Computer Science and Engineering.

Apply now

When applications open, you can apply online and will be expected to submit the following:

  • For all applicants, please upload your degree certificate and transcript of marks from your first degree (if you do not have your final results at the time of making your application, please upload a provisional certificate/interim transcript of marks). A transcript is required in order to have your application processed.
  • If your first language is not English, or you require a Tier 4 visa to study in the UK, please upload a Proof of English Proficiency if you have already obtained it. A list of accepted qualifications can be found here.
  • Please upload a detailed personal statement outlining why you wish to study this specific course, at City, University of London, as well as explaining how your past studies have prepared you for this course and how it will help you to progress in your career. If you require a Tier 4 student visa to undertake a Master's programme in the UK, then please note that the quality of your personal statement will also be taken into account by the visa issuing authorities when deciding to grant you a student visa or not.
  • If you are applying for a Part-time course, or have relevant work experience relating to the degree you are applying for, please upload a copy of your current CV/resume.

Please note: Academic references are not required when you submit your application. However, the admissions tutor may request them at a later date to help make a decision on your application.

Contact information for the Postgraduate Team

Tel: +44 (0)20 7040 0248
Email: smcsepg@city.ac.uk

Postgraduate Courses Office, A302
School of Mathematics, Computer Science & Engineering
City, University of London
Northampton Square
London
EC1V 0HB

Deep Learning
Study nature-inspired AI in our new high-tech City AI Lab.
£60,000
The median advertised salary for permanent jobs in Artificial Intelligence in the UK according to IT Jobs Watch.
During your course

More about fees

Fees in each subsequent year of study (where applicable) will be subject to an annual increase of 2%. We will confirm any change to the annual tuition fee to you in writing prior to you commencing each subsequent year of study (where applicable).

If a student leaves City after commencing but before completing their course, City reserves the right to charge the student the tuition/course fee for the full academic year (or full course for capacity limited post-graduate courses - up to a maximum of 2 years fees) in question. The student may be charged the full fee for that year or course as applicable unless the student is able to present justification that exceptional and unforeseeable reasons for their withdrawal exist.

How to pay

City has introduced an instalment payment scheme which is available to certain categories of students, including taught postgraduate students. For students following the normal academic year, the annual fee may be paid in two equal instalments: the first on registering, the second on 31st January. If you wish to pay your fees by instalment you must pay the first instalment at or before registration, by cheque or credit/debit card. You must also supply your bank details or credit card details for payment of your second instalment which will be deducted automatically from your bank or credit card account on 31st January.

Programme Director

Dr Eduardo Alonso - Programme Director, MSc in Artificial Intelligence

My colleagues and I are world-renowned experts in Artificial Intelligence. We've wanted to make this MSc available for years - and now there's enough computer capacity and enough data available to make an MSc in Artificial Intelligence focused on nature-inspired technology and Deep Learning viable.

Placements and internships

Our close contact with leading names in Artificial Intelligence, the Knowledge Quarter and Tech City gives you a head start when looking for an internship or placement.

The Professional Liaison Unit (within the School of Mathematics, Computer Science & Engineering) can help you contact companies where City has strong relationships and who may have opportunities for interns.

Academic facilities

The new City AI Lab contains the best possible computers, world-class facilities, the very latest software and tools, and the computational power needed for Deep Learning.

Accommodation

We offer a variety of accommodation options and support services for postgraduate students.

Read more about our postgraduate halls.

Our Accommodation Service can also help you find private accommodation.

Find out more about private accommodation.

Learn a language for free

We offer a free language course for City, University of London students.

Find out how to apply

Timetables

Course timetables are normally available from July and can be accessed from our timetabling pages. These pages also provide timetables for the current academic year, though this information should be viewed as indicative and details may vary from year to year.

View academic timetables

Please note that all academic timetables are subject to change.

Student support

We offer an extensive support network during your time here at City, University of London – from Learning Support (including disability support) and counselling to financial and career advice – leaving you free to enjoy every opportunity campus life has to offer.

Find out more about the different types of student support available.

Course content and assessment

Teaching and learning

You learn from recognised experts in applying Artificial Intelligence and Machine Learning to real-life problems through lectures, hands-on lab-based tutorials and coursework. Using tools and technologies that equip you to pursue the culmination of your MSc, you pursue a practical Artificial Intelligence project in your chosen application area.

Our teaching and learning methods mean your levels of specialist knowledge and learning autonomy increase as you work through the programme. Your guides are active researchers in AI from the Department of Computer Science. Guest lecturers from some of the biggest names in AI discuss the business aspects of running an AI company.

Each module is introduced in lectures. These give you examples, highlight the most important aspects of AI, and point you to complementary topics and study resources. You apply this material and develop your skills in laboratory sessions and tutorials, working on practical problem-solving exercises and theoretical questions. In the lab you can also see concepts and techniques in action, using the latest software, tools and environments.

Your personal tutor, a member of the academic staff, provides learning support and feedback throughout your course.

Assessment

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.

Modules

The programme has eight core modules. The course has been designed to adapt to developments in the sector, with space within the modules to explore your own interests, so there are no elective modules. In your third term, you undertake an individual project under the supervision of one of our AI experts.

Learning is hands-on through a mix of lectures, practical classes and workshops, with 30 hours teaching for each module (the exact balance varies for each module). You should also expect to spend around 120 hours of self-directed study for each module, completing exercises, checking your efforts and reading recommended literature.

The MSc in Artificial Intelligence has a particular emphasis on Deep Learning technology, based on neural networks and its applications, as well as computational modelling of learning and behaviour in neuroscience. The programme also explores the ethical and legal aspects of AI and its effects in society. The first term provides students with fundamental knowledge and skills in Artificial Intelligence at three levels: computational, algorithmic and implementational (the three Marr's levels). In the second term, students go on to specialise in cutting edge Deep Learning techniques and Reinforcement Learning.

Core modules

Introduction to Artificial Intelligence (15 credits)

  • Understand Artificial Intelligence methodologies and apply them to solve real-life problems
  • Devise Artificial Intelligence solutions using concepts and theories in neuroscience and evolutionary computation
  • Manage the design process and product development of Artificial Neural Networks
  • Critically assess the fundamentals of symbolic and Bayesian approaches to Artificial Intelligence

Programming and Mathematics for Artificial Intelligence (15 credits)

  • Formulate Artificial Intelligence problems mathematically
  • Develop Artificial Intelligence algorithms
  • Analyse and evaluate the complexity of Artificial Intelligence solutions
  • Test experimental hypotheses in an Artificial Intelligence context

Computational Cognitive Systems (15 credits)

  • Interpret in a systematic manner the value of different computational approaches to modelling cognition
  • Analyse criteria and specifications appropriate to modelling cognitive processes
  • Use appropriate tools for the design, implementation and test of computational models of cognition
  • Demonstrate comprehensive knowledge of end-to-end applications of error-correction models of learning and behaviour

Explainable Artificial Intelligence (15 credits)

  • Analyse and evaluate the interpretability of Artificial Intelligence algorithms
  • Implement accountable Artificial Intelligence methods, and select and deploy tools for post-hoc analysis
  • Examine ethical and legal issues related to the deployment of Artificial Intelligence systems
  • Apply explainable AI methods in actual application contexts

Deep Learning 1: Classification (15 credits)

  • Critically evaluate the main Deep Learning techniques for solving classification problems
  • Demonstrate detailed understanding of the basic principles of Convolutional Neural Networks and Deep Belief Networks
  • Develop and evaluate Deep Learning architectures as applied to the classification of large real-life datasets
  • Analyse alternative methods for Deep Learning classification

Deep Learning 2: Prediction (15 credits)

  • Critically evaluate the main Deep Learning techniques for solving prediction problems
  • Demonstrate detailed understanding of Recurrent Neural Networks
  • Develop and evaluate Deep Learning architectures as applied to the prediction and forecasting of dynamic time series
  • Analyse alternative methods for Deep Learning prediction

Deep Learning 3: Optimization (15 credits)

  • Critically evaluate Deep Learning optimization techniques
  • Demonstrate detailed understanding of Reinforcement Learning algorithms and how they are applied to optimization
  • Build Deep-Q Networks through the use of appropriate theory, practices and tools for their specification, design and evaluation
  • Analyse alternative methods for Machine Learning optimization

Agents and Multi-Agent Systems (15 credits)

  • Demonstrate in a systematic manner understanding of task environments and agent architectures
  • Analyse agent algorithms in terms of their computational complexity
  • Demonstrate comprehensive knowledge of Multi-Agent Systems and Game Theory
  • Critically evaluate the latest advances in Deep Learning within the context of transferability

Individual project

Solve a real-world problem using the tools and techniques acquired on the course.

You conduct your research largely independently, with academic supervision and, where appropriate, in collaboration with our industrial partners. You can also choose to carry out your MSc project as a six-month internship in a company.

The individual project is worth 60 credits.

The programme specification contains more information on how the course is organised, the requirements for progression for each part and credits required for awards.

After you graduate

Career prospects

Artificial Intelligence experts are highly sought after by businesses, including those working in health, finance, energy and transport, by neuroscience companies and by government. Employment opportunities range from AI developer jobs to roles that benefit from a deep understanding of cutting-edge Artificial Intelligence techniques and tools.

This programme's emphasis on nature-inspired AI and Deep Learning, and links with industrial partners at London's Tech City and the Knowledge Quarter, give students a particular advantage in finding work as specialists in AI companies and institutions.

The course also prepares students for entry into doctoral research.


Thank you for having decided to apply to study a postgraduate course at the School of Mathematics, Computer Science and Engineering.

Apply now

When applications open, you can apply online and will be expected to submit the following:

  • For all applicants, please upload your degree certificate and transcript of marks from your first degree (if you do not have your final results at the time of making your application, please upload a provisional certificate/interim transcript of marks). A transcript is required in order to have your application processed.
  • If your first language is not English, or you require a Tier 4 visa to study in the UK, please upload a Proof of English Proficiency if you have already obtained it. A list of accepted qualifications can be found here.
  • Please upload a detailed personal statement outlining why you wish to study this specific course, at City, University of London, as well as explaining how your past studies have prepared you for this course and how it will help you to progress in your career. If you require a Tier 4 student visa to undertake a Master's programme in the UK, then please note that the quality of your personal statement will also be taken into account by the visa issuing authorities when deciding to grant you a student visa or not.
  • If you are applying for a Part-time course, or have relevant work experience relating to the degree you are applying for, please upload a copy of your current CV/resume.

Please note: Academic references are not required when you submit your application. However, the admissions tutor may request them at a later date to help make a decision on your application.

Contact information for the Postgraduate Team

Tel: +44 (0)20 7040 0248
Email: smcsepg@city.ac.uk

Postgraduate Courses Office, A302
School of Mathematics, Computer Science & Engineering
City, University of London
Northampton Square
London
EC1V 0HB

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