The Master of Science in ICT aims to provide areas of excellence in the field of ICT that are suitable for the Information and Communications industry. The M. Sc. ICT aims to instil a high-level knowledge in the areas of expertise with additional focus on fostering research and development of new ideas in these areas.
The Course shall be open to applicants in possession of one of the following qualifications:
(a) the degree of Bachelor of Science (Honours) in any area of study deemed relevant by the Board or
(b) the degree of Bachelor of Engineering (Honours).
The admission requirements are applicable for courses commencing in October 2020.
For more detailed information pertaining to admission and progression requirements please refer to the bye-laws for the course available here.
UM currently hosts over 1,000 full-time international students and over 450 visiting students. The ever-increasing international students coming from various countries, in recent years, have transformed this 400-year old institution into an international campus.
Our international students generally describe Malta as a safe place, enjoying excellent weather and an all-year varied cultural programme. Malta is considered as the ideal place for students to study.
After you receive an offer from us, our International Office will assist you with visas, accommodation and other related issues.
Total Enrolment Fees: Eur 400 Yr 1: NIL - Yr 2: Eur 400
Total Tuition Fees: Eur 26,800 Yr 1: Eur 13,400 - Yr 2: Eur 13,400
The M.Sc. ICT (Signal Processing and Machine Learning) seeks to give a solid understanding of the theory, practice and the current research status in signal processing and machine learning tools, and their application in specific domains. Through a selection of core and advanced elective topics students will be able to select the areas of greatest interest leading to the M. Sc. Dissertation. Overall learning outcomes include:
• an understanding of the mathematical basis and engineering concepts, as well as a comparison of techniques currently in use. • ability to select and combine a subset of the techniques learnt to hypothesise a solution to a specific real-world or synthesised problem. • familiarity with software and hardware tools that are currently available for the development of signal processing and machine learning solutions. • an appreciation of research methods necessary to publish in these areas, enabling students to follow research as a professional job.
This course is a second cycle degree programme intended for graduates having a science or engineering background and are interested in: advancing the science of signal processing and machine learning, applying signal processing and machine learning techniques to every day real-world problems, and for practitioners working in domains where signal processing and pattern recognition are key to the technologies being developed or used.
M.Sc. ICT graduates specialising in Signal Processing and Machine Learning find employment in various sectors of the industry, including but not limited to: manufacturing, finance, game development, embedded systems, and software development. Furthermore, the knowledge and skills attained during this course open doors for graduates to seek employment with large research groups in industry, research institutes, and universities abroad.
This degree enables also further studies leading to a doctorate degree.
Click here to access the Programme of Study applicable from 2020/1.
Last Updated: 30 September 2020
The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication. The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. Unless for exceptional approved reasons, no changes to the programme of study for a particular academic year will be made once the students' registration period for that academic year begins.