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COURSE TITLE Master of Science in Information and Communication Technology (Signal Processing and Machine Learning)
 
COURSE CODE PMSCISPMFTT4

POSTNOMINAL

LEVEL OF QUALIFICATION

NATIONAL QUALIFICATIONS
FRAMEWORK LEVEL

DURATION

MODE OF ATTENDANCE

TOTAL ECTS CREDITS

M.Sc. ICT(Melit.)

Second Cycle

Level 7

4 Semesters

Full-time

120

COURSE OVERVIEW
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.
 
LEARNING OUTCOMES 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.
 
CAREER OPPORTUNITIES AND ACCESS TO FURTHER STUDY 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.
 
COURSE INTENDED FOR 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.
 
ADMISSION AND
PROGRESSION REQUIREMENTS
The Course shall be open to applicants in possession of one of the following qualifications:

(a) the degree of Bachelor of Science (Honours) in Information and Communication Technology or

(b) the degree of Bachelor of Science in Information Technology (Honours) or

(c) the degree of Bachelor of Science (Honours) in two areas of study, one of which is an area related to ICT or

(d) the degree of Bachelor of Engineering (Honours) in a suitable area of study or

(e) the degree of Bachelor of Science in two areas of study, one of which is an area related to ICT or

(f) a degree with a strong ICT component comparable to the degrees listed in (a) to (e).

Preparatory Programme

Applicants registering under paragraphs (e) and (f) shall be required to complete a preparatory programme comprising not less than 30 credits and not more than 60 credits as directed by the Board, obtained with an average mark of 55% or better, prior to their registration as regular students on the Course.

Preparatory programmes of study shall also be governed by the Principal Regulations.

The admission requirements are applicable for courses commencing in October 2015.

For more detailed information pertaining to admission and progression requirements please refer to the bye-laws for the course available here.
 
 


 

 

 
Last Updated: 27 June 2016
 
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.

For applicable fees please check the link on the Finance Office webpage.
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