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    The department of Intelligent Computer Systems is proud to offer a Masters degree programme that accommodates a variety of student requests.

    • Different Streams
      • Creative Technologies
      • Big Data
      • Artificial Vision
      • Automation
      • Fintech

     

    Overview 

    The Master of Science in Artificial Intelligence is a degree course in one specific branch of ICT that deals with simulating intelligence within real-world applications. This degree course has been purposely designed for working professionals, as well as, graduates who have just completed their undergraduate degree to form a strong and deep understanding of AI topics and eventually either converge into a possible proposed thematic area (Big Data, Creative Technologies, Automation, Artificial Vision or Fintech) or simply a generic advanced AI domain, before proceeding to a thesis. The programme has been purposely flexibly designed as to available for those who would like to intensely work to complete it full-time within a calendar year, or part-time over 2 years, while accommodating those candidates who have a day job. Finally, this Masters is intended to appeal and address current and future industry demands and niches by allowing the possibility of internships with industry partners as part of applied projects and/or the final project. 


    Learning Outcomes

    The core first part of the Master of Science in Artificial Intelligence ensures that students will:

    1. Be able to apply their previous knowledge from their undergraduate degree to applied intelligent computer systems;
    2. Relate statistical and data theories and applications to basic intelligent systems;
    3. Gain insightful and practical knowledge that will later apply to specific focuses like big data analytics, creative technologies, artificial vision, automation and fintech;
    4. Acquire basic skills that will help them through the second part of the course but also to employ them in everyday life involving big data, creative technologies, artificial vision, automation and fintech.

    In the second part of the course the students can focus on five distinct research domains that each carries a specific programme rational and learning outcomes.

     

    The Big Data Analytics stream focuses on a strong theoretical background in machine learning, statistics, and data mining with advanced knowledge of computational and statistical data analysis. An advanced knowledge and appreciation of non-statistical approaches to data and distributed systems and large scale databases also forms an integral part of this stream. Finally, an appreciation of how the role of a data analyst or scientist fits into the organisational and development processes of a company is covered.

    The learning outcomes for this big data stream are:

    • a highly analytical approach to problem solving;
    • ability to extract value and insight from data;
    • ability to analyse and critically evaluate applicability of both machine learning, statistical and data mining approaches;
    • ability to work with big amounts of structured and unstructured data.

     

    The Creative Technologies stream focuses on smart technologies that are becoming increasingly important for the creative industries. The skills associated with the once-separate creative and technical worlds are beginning to overlap more and more, especially with the rise of smart interfaces and wearable devices. The scope of this Masters focus stream is to serve as a link between these two worlds thus creating professionals capable of bridging the gap which exists between the two.

    Students will:

    • Be prepared for a career as technology-led experts in the creative industries;
    • Learn how to design, develop and apply software in various areas of the creative industries;
    • Be aware of the fundamental concepts behind intelligent computing;
    • Have a clear sense of the issues involved in building and maintaining reliable software for the sophisticated demands of today’s market;
    • Understand the social context and visual design aspects of software development.


    The Artificial Vision stream focuses on the state –of-the-art techniques that extract information from images and videos. Artificial vision is proving to be crucial in various industrial applications, such as manufacturing (eg. Visual quality inspection), entertainment (eg. Capture body movement with Kinect sensor), robotics (eg. Exploring a new place), health (eg. Medical image processing), and security (eg. Pedestrian and car tracking), among others.

    Students will:

    • Gain broad knowledge on various state –of the-art algorithms
    • Understand how the visual system of the brain processes visual information
    • Understand the challenges of artificial vision algorithms in real-world applications
    • Develop hands on experience in the implementation of various algorithms using Matlab/Python
    • Develop the ability to analyse and critically evaluate applicability of artificial vision algorithms for given problems
    • Be prepared for a career in the vision-based industries
    • Have the opportunity of a research internship with another European University.


    The Automation stream offers different facets of Artificial Intelligence, bringing together aspects of Robotics, Natural Language Processing and Artificial Vision. Automation is an ever growing industry in AI and, through this stream, you will receive applied, hands-on training in preparation to meet both industry demands, as well as gain the necessary knowledge to undertake research in this exciting field. Robot/Machine-Human interaction is becoming ubiquitous in our everyday devices. 

    Students will: 

    • Understanding of embedded and control systems
    • Understand the technologies used by a machine to understand, process and generate language
    • Understand the technologies used in vision processing and how images can be classified
    • Be able to implement solutions to different AI problems.


    The Fintech stream will provide students with the core elements of financial technologies and will educate them on how to digitally transform business operations using AI techniques. In addition, students will obtain deeper knowledge of financial systems, artificial intelligence, and big data analytics. The use of emerging technologies like Blockchain and Cryptocurrencies will also be covered. Fintech is quickly driving efficiency up and costs down through to the digitalisation of transactions thus creating a cross-disciplinary science. The course will equip students with the essential skills and knowledge for a career in this field; it combines theory, intensive practice and industrial engagement. The initiative is also expected to contribute significantly to the digital transformation of the country’s financial services industry especially since Malta is aiming to become a Finetech hub in the coming years.

    Students will:

    • Gain broad knowledge on various state-of-the-art algorithms;
    • Understand the challenges of Fintech in real-world applications;
    • Develop a highly analytical approach to problem-solving; 
    • Learn to extract value and insight from data; 
    • Seek to analyse and critically evaluate applicability of both machine learning, statistical and data mining approaches within the context of Fintech; 
    • Develop hands-on experience in the implementation of various Fintech algorithms;
    • Develop the ability to analyse and critically evaluate applicability of Fintech algorithms for given problems;
    • Be prepared for a career in the Fintech industries.


    Career Opportunities and Access to Further Study

    On successfully completing the Master of Science in Artificial Intelligence, the post-graduates can further pursue their studies towards a PhD or apply their acquired knowledge to their line of work by fruitfully applying either creative technologies, big data analytics, artificial vision, automation or fintech to their line of work. Alternatively, new possibilities to switch to a fresh career within these three areas is possible as current industry needs are indicating a need and a strong potential to employ professionals with strong understanding and expertise within the three streams being offered.

     

    Course Intended for

    The Master of Science in Artificial Intelligence appeals to all graduates from a degree which has a strong ICT component, but the board of studies will also take into consideration candidates with a strong experience track record evidenced by a substantial portfolio of work in industry.

     

    Tuition Fees for all Postgraduate courses.

     

    Course related Information

    1. Full-time Programme of Studies
    2. Part-time Programme of Studies
    3. Applying Online

    4. Schedule of Tasks - M.Sc. in AI (Research Full-time) 2015/6
    5. Schedule of Tasks - M.Sc. in AI (Research Part-time) 2015/6

    6. Schedule of Tasks - M.Sc. in AI (Research Full-time) 2016/7
    7. Schedule of Tasks - M.Sc. in AI (Research Part-time) 2016/7

    8. Proposed Titles & Areas of Interest

    9. Supervision Declaration Form (ICS5200) 2016/7
    10. Dissertation Proposal Form (ICS5200) 2016/7

    11. ICS5200 Project Allocations - M.Sc. in AI (Research Full-time) 2015/6
    12. ICS5200 Project Allocations - M.Sc. in AI (Research Part-time) 2015/6


    13. Important Aids

    All classes have been transferred after 5pm to accommodate student requests


    MSCAI1



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    email: ai@um.edu.mt OR ics@um.edu.mt

     

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    Last Updated: 28 April 2017

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