Last Updated on August 11, 2023 by Oluwajuwon Alvina

Artificial Intelligence and Machine Learning Masters/MSc

Start dateSeptember/OctoberDuration1 year full-timeCourse TypePostgraduate, TaughtFeesWe charge an annual tuition fee. Fees for 2020/21: 
£9,900 (UK/EU students) 
£24,120 (International Students)
Further fee and scholarships information is available.Visit usRequest a course prospectusApply now

Understand the fundamental principles of Artificial Intelligence and Machine Learning. This specialist Artificial Intelligence Masters/MSc programme will allow you to apply your knowledge to real problems.

Online chat event

THURSDAY 2 JULY 2020 11:00 – 15:00
Our online chat events are designed to inform prospective postgraduate students, applicants and offer-holders about the postgraduate courses available within the School of Computer Science and how to prepare you for your course. Find out more:Online chat further informationThe past ten years have seen astonishing advances in Artificial Intelligence and Machine Learning that are promising to transfer the way we interpret and use data. These advances are already finding their way into our daily lives in areas that include automated language translation, speech recognition and generation, recommender systems, face identification and other applications that we may not even be aware of. It is also allowing us to think about the nature of intelligence from different perspectives to understand the way that humans perform tasks, and to augment and support our abilities in areas such as medical diagnostics, where AI techniques are beginning to be used to filter vast medical datasets to provide doctors with new insights that can be used to inform a diagnosis or treatment plan.

On this programme you will learn about the fundamental principles of AI and ML and how machines can perceive, explore, and understand the world around us. You will extend and apply your knowledge to real problems in a substantial individual project working with one of our world-leading researchers, many of whom are working closely with the Alan Turing Institute, the UK national institute for AI and Data Science, of which the University of Birmingham is a member. You will learn about what current generation AIs can and cannot do, about contemporary challenges, and about societal and ethical considerations so that you can make informed decisions about how AI techniques should be used in the real world.

You will study a range of compulsory modules and be able to choose from a variety of optional modules, whilst also undertaking an Artificial Intelligence and Machine Learning Project.

Why study Artificial Intelligence Masters/MSc at Birmingham

  • Birmingham is one of the leading universities in the country for postgraduate study in computer science, and we are proud to deliver outstanding programmes that offer a range of exciting career opportunities for students from around the world.
  • State-of-the-art, multi-million pound facilities include dedicated laboratories for Computer Science students, a teaching laboratory for Robotics, and research laboratories for Security, Medical Imaging, Intelligent Robotics and Computer Vision.
  • We are a partner in the Alan Turing Institute, the UK’s national institute for data science and artificial intelligence.

Award-winning development

At the School of Computer Science we are not just renowned for teaching and research excellence. We also produce novel solutions for real-world applications, including:

  • Working with Jaguar Land Rover to make their vehicles more secure
  • Contributing to the development of the Trusted Platform Module which makes many of our computers capable of secure cryptographic operations
  • Deploying autonomous, intelligent robots in security and health support facilities
  • Developing a revolutionary, award-winning method for diagnosing skin cancer

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Modules

The course consists of 180 credits. As well as 2 x 20 credit compulsory modules and 1 x 60 credit compulsory project, you also have the chance to choose up to 80 credits from a range of optional, specialist modules.

Core modules

  • Artificial Intelligence and Machine Learning Project – 60 credits
  • Current Topics in Artificial Intelligence and Machine Learning – 20 credits
  • Mathematical Foundations of Artificial Intelligence and Machine Learning – 20 credits

Optional modules

40-80 credits must be chosen. Example modules:

  • Complex Adaptive Systems (Extended) – 20 credits
  • Computer Vision and Imaging (Extended) – 20 credits
  • Intelligent Robotics (Extended) – 20 credits
  • Machine Learning and Intelligent Data Analysis (Extended) – 20 credits
  • Robot Vision – 20 credits

0-40 credits must be chosen. Example modules:

  • Programming in Python – 20 credits
  • Research Skills, Evaluation Methods and Statistics – 20 credits
  • Storing and Managing Data – 20 credits
  • Visualisation – 20 credits

Please note: The modules listed on the website for this programme are regularly reviewed to ensure they are up-to-date and informed by the latest research and teaching methods.

Fees

£2,000 fees scholarships available for Masters courses starting in September 2020.Find out more

Annual tuition fees for 2020/21

  • UK/EU students: £9,900
  • International students: £24,120

Learn more about fees and funding.

Postgraduate Loans (PGL) for Masters students

UK and EU students looking to pursue a Masters programme in the UK can apply for a non-means-tested loan from the British government via the Student Loans Company.

A loan of up to £11,222 is available to students applying to taught and research Masters courses (loan amount for 2020 entry).

Learn more about applying for PGL 

Scholarships and studentships

We offer a range of postgraduate scholarships for taught programmes and research opportunities to ensure the very best talent is nurtured and supported at postgraduate level.

Additional scholarships can be found in the funding database.

Contact the department for further information.

For further information about scholarships for our postgraduate taught programmes visit www.cs.bham.ac.uk/admissions/postgraduate-taught/scholarships/


For students applying for the 2020/21 academic year

The UK Government has confirmed that EU students will continue to be eligible for ‘home fee status’ for entry in September 2020, and will continue to have access to financial support available via student loans for the duration of their course. For more information take a look at the gov.uk website.

How To Apply

International applicants requiring visas

Please note that applications to this programme from students who are international for fees will close on 1 July 2020. We will close applications as soon as the programme is full, early applications are encouraged.

UK/EU and non-Tier 4 applicants

Applications will close on 10 September 2020. We will close applications as soon as the programme is full, early applications are encouraged.

Before you make your application

You will need to provide a transcript of your studies to date. This should include details of modules and subjects studied, and grades already obtained. We are unable to proceed with your application without this information, and if it is not provided, your application could be made unsuccessful.

You may wish to register your interest with us to receive regular news and updates on postgraduate life within this Department and the wider University.

If you are made an offer

If you are made an offer, you will have 28 days to accept the offer via the online portal, or it will automatically be declined by default.

Making your application

When clicking on the Apply Now button you will be directed to an application specifically designed for the programme you wish to apply for where you will create an account with the University application system and submit your application and supporting documents online. Further information regarding how to apply online can be found on the How to apply pages

Apply now

Why this course?

Machine learning and deep neural network systems are currently used by leading organisations worldwide and research centres in a wide range of applications and products. This course is for engineers and scientists looking to gain the necessary skills to be able to design these systems for use in industry.

Our MSc Machine Learning & Deep Learning degree focuses on state-of-the-art technologies for machine learning and deep neural network systems. The emphasis is on architectures, algorithms and implementation with applications in a diverse range of areas.

Delivered jointly by the Departments of Electronic & Electrical Engineering and Computer & Information Sciences, you’ll be exposed to state-of-the-art engineering and software technologies that underpin machine learning and deep neural network systems.

You’ll learn about and gain experience from hands-on, industry relevant projects and examples. This includes programming languages and engineering tools used in an increasing number of products and services worldwide.

Machine learning and deep learning concept - Brain made with shining wireframe above multiple blockchain cpu on circuit board 3d render
THE Awards 2019: UK University of the Year Winner

What you’ll study

You’ll complete six classes over two semesters comprising compulsory and elective taught classes. These are followed by a three-month research project in a chosen area.

If you’ve previously taken a similar class to one of the compulsory classes, you’ll be offered an alternative.

MSc industrial internships

You’ll also have the opportunity to complete the project through our competitive MSc industrial internships. These are offered in collaboration with selected industry partners.

You’ll address real-world engineering challenges the partners are facing, with site visits, access, and provision of relevant technical data and/or facilities provided. You’ll also have an industry mentor and an academic supervisor.

Industry engagement

Interaction with industry is provided through our internships, teaching seminars and networking events. Companies such as Leonardo, Comcast (Sky), ORE Catapult, PNDC, Xilinx, Texas Instruments, MathWorks, NHS, Canon Medical Research and Varian Ltd are just a few examples of the industry partners you can engage with during your course.

Facilities

The Departments have excellent teaching facilities including interactive classrooms and state-of-the-art laboratories with the latest computing equipment. You’ll have the opportunity to engage with academics and researchers in our Machine Learning and Neuromorphic Technology Unit.

You’ll also have access to our IT facilities, including web-based resources, wireless internet and free email. An IT support team is available to help with all your needs.

The Queen's Anniversary Prizes for Higher and Further Education 2019.
QS Stars, Rated for Excellence - 5 stars.
The Times & Sunday Times Good University Guide 2020 - Scottish University of the Year.

Course content

Autonomous Sensing, Reasoning & Deep Learning
Digital Signal Processing Principles
Big Data Technologies (20)
Machine Learning for Data Analytics
Assignment & Professional Studies

Learning & teaching

Our teaching and learning methods ensure you’ll develop not only technical engineering expertise but also communications, project management and leadership skills.

Teaching and learning methods include interactive lectures, problem-solving tutorials and practical project-based laboratories. Our technical and experimental officers are available to provide support and guidance.

For each module, you’ll have approximately five hours of direct teaching per week. In addition, you’re expected to undertake a further five to six hours of self-study, using our web-based virtual learning environment (Myplace), research journals and library facilities.

In some classes, you’ll undertake group projects. These will help to develop your interpersonal, communication and transferable skills essential to a career in industry.

Assessment

Each module has a combination of written assignments, individual and group reports, oral presentations, practical lab work and, where appropriate, an end-of-term exam.

Assessment of the summer research project consists of four elements, with individual criteria: Interim Report, Poster/Demonstration Presentation, Final Report and Conduct.

Entry requirements

Academic requirementsNormally a first-class or second-class honours degree (or international equivalent) in electronic or electrical engineering, or computer science.Highly-qualified candidates from other relevant engineering or science-related disciplines may be considered.

Pre-Masters preparation course

The Pre-Masters Programme is a preparation course held at the University of Strathclyde International Study Centre, for international students (non EU/UK) who do not meet the academic entry requirements for a Masters degree at University of Strathclyde. The Pre-Masters programme provides progression to a number of degree options.

Upon successful completion, you will be able to progress to this degree course at the University of Strathclyde.

International students

We’ve a thriving international community with students coming here to study from over 100 countries across the world. Find out all you need to know about studying in Glasgow at Strathclyde and hear from students about their experiences.Visit our international students’ section

Map of the world.

Fees & funding

2020/21

All fees quoted are for full-time courses and per academic year unless stated otherwise.

Scotland/EU£8,100
Rest of UK£9,250
International£20,900
Additional costsCourse materials & costsThe department provides a service whereby printed notes are available to the students subject to a small charge to cover copying costs. Students are recommended/required to have copies of such notes but we provide access to both printed copies and e-copies. The latter are provided without charge – in accordance with University policy. Any printed material that is mandatory (in that form) is provided with no additional charge to the students. Expect that students pay around £100 for additional course materials and books.Placements & field tripsThe department and student societies support a number of industrial visits throughout the year. These trips are not mandatory for specific programmes and modules and any incurred charge to cover transport is either met by the students or by the department.Other costsStudents are not required to purchase any specific software licenses – all software used is available on campus machines, either locally or remotely.All undergraduates and PGI students are provided for the duration of their course with student-membership of IET (Professional Body) paid for by the department.Some hardware (micro controllers, design boards) may be made available to students for loan subject to appropriate refundable deposit. Students may consider purchase of low cost microcontroller boards for project work – cost from £10-£30.Access to EEE Computer labs out of working hours is via card access – card cost is £20 – refundable on return of card.
Students are provided with an additional print-quota for use in EEE labs for EEE classes conducted in EEE computer labs. (Paid top-ups possible via University IT services.)Expected printing and report binding costs are around £10-£15 a year – will depend upon exact programme and class assignments. Binding is provided at cost (50p to £1.00) by EEE Resource Centre in R4.01.
Available scholarshipsTake a look at our scholarships search for funding opportunities.

Please note: the fees shown are annual and may be subject to an increase each year. Find out more about fees.

How can I fund my course?

Scottish and non-UK EU postgraduate students

Scottish and non-UK EU postgraduate students may be able to apply for support from the Student Awards Agency Scotland (SAAS). The support is in the form of a tuition fee loan and for eligible students, a living cost loan. Find out more about the support and how to apply.

Don’t forget to check our scholarship search for more help with fees and funding.

Data Lab Scholarship

The Data Lab is a collaborative programme between The Data Lab and eleven Scottish universities, including Strathclyde. It facilitates industry involvement and collaboration, and provides full funding and resources for students. A number of scholarships are available for Scottish/EU students studying this course. Find out more

Students who wish to be considered for these scholarships need to ensure that they fulfil the eligibility criteria set out by the Scottish Funding Council (SFC).

Applicants do not need to submit a separate application form to be considered for one of the Data Lab Scholarships. The Departments Admissions Panel will review all applications submitted by the deadline date of 31 July, with all eligible applicants automatically considered for these scholarships.

The scholarships will be awarded on a competitive basis, taking into consideration academic performance, references and any other relevant information. Applicants should ensure that all information they wish to be considered by the Panel, has been included in their MSc application. Successful candidates will be advised of their scholarship award by 12 August.

Faculty of Engineering Excellence Scholarship (FEES) for International Students

If you’re applying for an MSc course you’ll be eligible to apply for a Faculty of Engineering Excellence Scholarship offering up to £3,000 towards your tuition fees.

The scholarship is available for application to all self-funded, new international (non-EU) fee paying students holding an offer of study for an MSc programme in the Faculty of Engineering at the University of Strathclyde. Please note you must have an offer of study for a full-time course at Strathclyde before applying.

You must start your full-time MSc programme at Strathclyde in the coming academic year (2019-20).Find out more

Careers

Job titles for future graduates of th MSc Machine Learning & Deep Learning include (but not limited to):

  • Graduate Software Engineer
  • Electronic Engineering Systems Analysts
  • Lecturer / Researcher
  • Data Scientist
  • Data Engineer
  • Data Analyst
  • Machine Learning Engineer
  • Data Insight Analyst

Glasgow is Scotland’s biggest & most cosmopolitan city

Our campus is based in the very heart of Glasgow, Scotland’s largest city. National Geographic named Glasgow as one of its ‘Best of the World’ destinations, while Rough Guide readers have voted Glasgow the world’s friendliest city! And Time Out named Glasgow in the top ten best cities in the world – we couldn’t agree more!

We’re in the city centre, next to the Merchant City, both of which are great locations for sightseeing, shopping and socialising alongside your studies.

Find out what some of our students think about studying in Glasgow!Find out all about life in Glasgow

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