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MSc APPLIED ARTIFICIAL INTELLIGENCE

UK Fees

£12000

Int. Fees

£17900

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Overview

Artificial Intelligence is becoming increasingly common in the modern world and there is a constant and sustained need for professionals who have the expertise and training needed to understand AI technologies and to use them responsibly. Additionally, from a societal perspective, it is crucial that citizens of the future have a basic understanding of AI concepts so that they can engage both effectively and critically with AI systems which are becoming a constant presence in our daily lives

To meet the growing need for AI, experts and AI-educated professionals this MSc in Applied Artificial Intelligence aims to convert graduates into AI specialists who are able to meet the demands of industry and society in AI, with particular emphasis on crucial areas such as smart manufacturing and industry 4.0, natural language processing and computer vision.

The course is uniquely designed for both graduates or practitioners from a computing and non-computing background, wishing to pursue a career in the development of machine learning and artificial intelligence solutions to practical problems and addresses the latest developments in machine learning and artificial intelligence through a rich series of seminars from experts in the field.

Mode Duration Start date Application code Application method
ModeFull-time Duration2 years Start dateJanuary Application code5795 Application method Direct to LSBU
ModeFull-time Duration1 year Start dateSeptember Application code5794 Application method Direct to LSBU
ModePart-time Duration2 years Start dateSeptember Application code5796 Application method Direct to LSBU

Course Accreditations

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Location

London South Bank University student union is located at 103 Borough Rd, London SE1 0AA.

If you are visiting our Southwark Campus, you may wish to use our downloadable campus map (PNG File 466 KB). For information on accessibility, see our DisabledGo access guides. See our location page for more details.

Entry Level Requirements

  • 2:2 UK honours first degree or international equivalent in any subject
  • A GCSE Grade 4 in Mathematics or equivalent
  • A GCSE Grade 4 in English or equivalent
  • We recognise that many people have a wealth of valuable skills and knowledge they've developed at work or through training. If candidates have the potential to succeed in postgraduate or post-experience studies we'll consider their application on its individual merit. Applications may be considered where candidates demonstrate a combination of educational qualifications and work experience.
  • We welcome qualifications from around the world. English language qualifications for international students: IELTS score of 6.5.
  • After admission, prospective students can apply for the accreditation of prior experiential learning (APEL), following the approved School of Engineering procedure.

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Missing English and Maths qualifications?

If you do not have the required English and Maths qualifications needed to satisfy the entry requirements for this programme, we have courses available at our partner College that you can take to upskill in these areas. Find out more at South Bank College.

United Kingdom

£12000

Tuition fees for home students

International

£17900

Tuition fees for international students

Tuition fees are subject to annual inflationary increases. Find out more about tuition fees for Undergraduate or Postgraduate courses.

  • Part-time

    part-time

    MSc Applied Artificial Intelligence (PT) - Year 1

    The fee shown is for entry 2024/25
    UK fee: £5333.33 International fee: £7955.56
    AOS/LSBU code: 5796 Session code: 1PS00
    Total course fee:
    UK: £12000
    International: £17900

    MSc Applied Artificial Intelligence (PT) - Year 2

    The fee shown is for entry 2024/25
    UK fee: £6666.67 International fee: £9944.44
    AOS/LSBU code: 5796 Session code: 2PS00
    Total course fee:
    UK: £12000
    International: £17900

  • Full-time

    full-time

    MSc Applied Artificial Intelligence (FT) - Year 1

    The fee shown is for entry 2024/25
    UK fee: £12000 International fee: £17900
    AOS/LSBU code: 5794 Session code: 1FS00

    MSc Applied Artificial Intelligence (FT) (JAN) - Year 1

    The fee shown is for entry 2024/25
    UK fee: £12000 International fee: £17900
    AOS/LSBU code: 5795 Session code: 1FS00

For more information, including how and when to pay, see our fees and funding section for postgraduate students.

See our Tuition Fees Regulations (PDF File 391 KB) and Refund Policy (PDF File 775 KB).

Possible fee changes

The University reserves the right to increase its fees in line with changes to legislation, regulation and any government guidance or decisions.

The fees for international students are reviewed annually and the University reserves the right to increase the tuition fees in line with the RPIX measure of inflation up to 4 per cent.

Postgraduate loan (PGL) for Masters study

If you are starting a Masters course, studying either full- or part-time, you may be entitled to apply for a postgraduate study loan. Find out more at our postgraduate fees and funding section.

Scholarships

We offer several types of fee reduction through our scholarships and bursaries. Find the full list and other useful information on funding your studies on the scholarships and fee discounts page.

Fee status

Please check your fee status and whether you are considered a Home, EU or International student for fee-paying purposes and for our regulatory returns, by reading the UKCISA regulations.

Home

Mode Duration Start date Application code Application method
Mode Full-time Duration 2 years Start date January Application code 5795 Application method Direct to LSBU
Mode Full-time Duration 1 year Start date September Application code 5794 Application method Direct to LSBU
Mode Part-time Duration 2 years Start date September Application code 5796 Application method Direct to LSBU

Postgraduate students and research students should apply through our dedicated application system. Full details of how to do this are supplied on our How to apply section for postgraduate students and our How to apply section for research students.

See our admissions policy (PDF File 1,043 KB) and complaints policy (PDF File 516 KB).

Accommodation

Students should apply for accommodation at London South Bank University (LSBU) as soon as possible, once we have made an offer of a place on one of our academic courses. Read more about applying for accommodation at LSBU.

Finance

It's a good idea to think about how you'll pay university tuition and maintenance costs while you're still applying for a place to study. Remember – you don't need to wait for a confirmed place on a course to start applying for student finance. Read how to pay your fees as a postgraduate student.

Prepare to start

We help our students prepare for university even before the semester starts. To find out when you should apply for your LSBU accommodation or student finance read the How to apply tab for this course.

Enrolment

Before you start your course we’ll send you information on what you’ll need to do before you arrive and during your first few days on campus. You can read about the process on our Enrolment pages.

  • Foundations of calculus, statistics, and optimization
    This module will cover the fundamental concepts and techniques from linear algebra, differential calculus and probability.
    The acquired tools will help the student to understand how AI is built and enable them to tailor standard methods to specific problems they will be facing and to interpret the results obtained through data analysis.
  • Python programming for AI and Visualization
    This module provides an intensive introduction to programming, especially for students without a computer science background.
    The module will cover the basics of program development in Python, with specific attention to its use in visualizing and exploring data, and in translating mathematical problems and models into a computational solution.
  • Machine Learning
    The module introduces you to the basic theory, concepts, and techniques of machine learning using Python. It will cover the main topics and essential theory in the area. The module also focuses on developing practical skills in designing and developing machine learning systems using suitable software and algorithms in order to solve real-world problems.
  • Deep Learning
    The module introduces neural networks and deep learning, one of the key topics in modern applied AI.
    The module will provide the student with an in-depth understanding of all the components of neural networks, from the different computational building blocks to the functions to be optimized and finally to the different optimization strategies.
    The module will present how neural networks can be trained and validated to learn from data to solve specific tasks, and how they evolved into deep neural networks, convolutional neural networks and graph networks, presenting their major architecture concepts.
  • Industrial Cyber-Physical Systems
    Industrial Cyber-Physical Systems (ICPS) are real-world networked industrial production systems having a cyber-representation through the digitalisation of data and information across the enterprise and value chain. This module offers a comprehensive overview of ICPS and outlines the challenges related to the fourth industrial revolution commonly referred to as Industry 4.0. The module consists of two parts. The first part will introduce the theoretical framework and supporting technologies of the fourth industrial revolution (e.g., industrial internet-of-things, digital twins, etc.). The second part focuses on system design and implementation aspects of ICPS along with multiple tutoring sessions.
  • Natural Language Processing
    The module covers theoretical and practical aspects of Natural Language Processing to design, develop and implement Collaborative and Cognitive Communication Systems for robotics while linking AI and NLP to human psychology patterns and applying it to Chabot’s, digital assistants and context-aware personalized interfaces. The lecture sessions will deliver state-of-the-art theories, models and algorithms covering neural Language models, speech tagging, Vector Semantics and Embedding, information extraction and sentimental analysis. The lab sessions will deliver hands-on practical sessions using Chabot frameworks, Python NLP libraries and tool kits for NLP.
  • Computer Vision and Pattern Recognitio
    The pervasive nature of visual tasks in everyday life, and the amount of imaging information accrued by mobile, wearable and classical devices, calls more and more for sophisticated tools able to relieve the burden of image scanning and screening from human users. Additionally, many task can benefit from image-guided augmented reality scenarios (e.g. surgery), or can be automated through visual-guidance (robotics).  
    The module covers the theoretical and practical aspects of image processing and analysis, image understanding and computer vision:
    after introducing the basics principles and concepts of image formation and image representation, it will present the fundamentals of image processing. It then will dive in modern approaches to the processing of images and videos: object detection, object recognition, scene understanding  using machine learning and artificial intelligence
  • Future Internet Technologies
    Future Internet technologies comprise set of enablers to deal with the limitation of the existing Internet. This includes but not limited All-IP Networking Architectures, the evolution towards 4G+/5G networking architectures, open-based networking technologies, Cloud Computing challenges and IoT technologies and its interworking with 4G+/5G networks. The module will provide both theoretical knowledge and practical exposure to the students.
  • Data Management
    Data Management and Data Quality are increasingly at the heart of every commercial and research enterprise, as the value of data increases along with the need for adaptive security. This module will give you a critical and evaluative knowledge of the theory, practice and research of software engineering techniques for Data Management amid today’s complex and changing business/commercial/research environments.
  • Data Mining and Analysis
    The module introduces you to the basic theory, concepts, and techniques of data mining, and its role in data science and business intelligence. It will cover the main topics in the area. The module also focuses on developing practical skills in solving real-world data mining problems by using appropriate software suites. Base SAS®, SAS® Enterprise Miner, SAS® Enterprise Guide and Tableau® may be taught and used for this purpose.
  • Robotics
    The module introduces students to the basic elements and principles of robotics. Essential geometric concepts of rigid-body displacements will be introduced and applied to the kinematic analysis of different machines.   Differential kinematics will be developed and applied to study the statics and dynamics of robots.  Some problems concerned with the control of these machines will be considered.
    Laboratory exercises are designed to consolidate understanding of robot kinematics and programming as well as giving an appreciation of practical considerations.
  • Ethics in AI and Seminars
    The module will provide students with the critical skills, knowledge and analytical abilities needed to identify and address ethical challenges as they arise in practice from the application of AI. The module will engage with the ethical and societal challenges of AI and is thoroughly informed by the knowledge, theories and methods of established academic disciplines from philosophy to computer science.
    Industrial seminars on AI applications will complement the content of the module, exposing the students to the challenges of developing an AI application, considering the short- and long-ranging societal fallout.
  • Research Methods
    The module provides students with the ability to discuss, evaluate and use a variety of research methods and techniques for their chosen subject area of Computer Science and Informatics and to develop a professional and ethical approach to carrying out research-based projects. It also equips students with entrepreneurial and innovation skills increasingly sought by industry and employers.

    NOTE: You will be required to pass the module before progressing to the Dissertation stage of your studies. In order to pass this module, students must obtain a weighted average grade of at least 50%.
  • Dissertation
    The module requires students to undertake an independent piece of research/development work, investigating in depth a subject, in which they have a particular interest and of their own selection. The dissertation assesses students’ ability to integrate information from various sources, to conduct an in-depth investigation, where necessary specify, appropriately develop bespoke software/technology-based solutions, to critically analyse results and information obtained and to propose improvements/further work. Each student will submit a dissertation of between 12,000-15,000 words.

All modules are assessed by a mix of coursework and examinations.

Careers

Employability Service

At LSBU, we want to set you up for a successful career. During your studies – and for two years after you graduate – you’ll have access to our Employability Service, which includes:

  • An online board where you can see a wide range of placements: part-time, full-time or voluntary. You can also drop in to see our Job Shop advisers, who are always available to help you take the next step in your search.
  • Our Careers Gym offering group workshops on CVs, interview techniques and finding work experience, as well as regular presentations from employers across a range of sectors.

Our Student Enterprise team can also help you start your own business and develop valuable entrepreneurial skills.

Career opportunities range from IT services to business consultancy, and this course will prepare you for a career in the business intelligence community working actively with a range of resources including tools from major commercial vendors such as Microsoft and SAS.

As a graduate of this course you should to be able to work within the areas of business intelligence or business and data analytics, in roles such as a business intelligence specialist, data or business analyst or business intelligence developer.

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Contact information

Course Enquiries - UK

Tel: 0207 815 7500