Master of Science in Signal Processing and Machine Learning [Taught and Research (Mainly Taught)]

MQF Level

Duration and Credits

3 Semesters

90 ECTS

Mode of Study

Full-time

This programme of study is also offered on a part-time basis. Please consult the Registrar鈥檚 website for more information pertaining to courses offered by the University.

The Master of Science in Signal Processing and Machine Learning aims to instill a high-level knowledge in the areas of Signal Processing and Machine Learning with additional focus on fostering research and development of new ideas in these areas. The M.Sc. in 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 you will be able to select the areas of greatest interest leading to the M. Sc. Dissertation.

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福利在线免费 for International applicants

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The Course shall be open to applicants in possession of one of the following qualifications: (a) the degree of Bachelor of Science in 福利在线免费 Technology (Honours) - B.Sc. I.T. (Hons) - with at least Second Class Honours or (b) the degree of Bachelor of Science (Honours) in 福利在线免费 and Communication Technology - B.Sc. (Hons) I.C.T. - with at least Second Class Honours or (c) the degree of Bachelor of Science (Honours) in Computing Science or in Computer Engineering - B.Sc. (Hons) - with at least Second Class Honours, provided that for the degree in Signal Processing and Machine Learning, other areas of study deemed relevant by the Board may also be considered or (d) the degree of Bachelor of Engineering (Honours) - B.Eng.(Hons) - with at least Second Class Honours in a suitable area of study or (e) any other Honours degree with a strong ICT component which the Board deems comparable to the qualifications indicated in (a), (b), (c) or (d) or (f) a Third Class Honours degree in an ICT related area of study together with a professional qualification/s or experience as evidenced by a substantial portfolio of recent works, deemed by the University Admissions Board, on the recommendation of the Faculty Admissions Committee, to satisfy in full the admission requirements of the Course or (g) any other Honours degree obtained with at least Second Class Honours, provided that applicants would have successfully completed at least three individual study-units as directed by the Board, prior to being admitted to the Course. The admission of applicants under paragraph (f) may be made conditional on the results of an interview conducted for the purpose. Interviews, when necessary, shall be conducted by a board composed of at least three members. Eligible applicants in terms of paragraphs (a) to (f) may register as visiting students for individual study-units, as directed by the Board, and obtain credit for them. Should applicants be accepted to join the Course within 5 years from following the first study-unit, the Board may allow the transfer of credits to the student鈥檚 academic record for the Course in lieu of comparable units in the current programme for the Degree.

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You can submit your application online. The deadlines for submission of applications vary according to the intake and courses. We encourage all international applicants to submit their applications as soon as possible. This is especially important if you require a visa to travel and eventually stay in Malta.

You can compare your national qualifications to the local requirements by visiting our qualifications comparability webpage. Access more information about our admission process and English language requirements.

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Our dedicated team at the student recruitment office is here to support you every step of the way. From the moment you start your application to the moment when you receive your decision letter, we're here to assist you. If you have any questions or need further information, don't hesitate to reach out to us. You can contact us at info@um.edu.mt, and our team will be more than happy to help.

After you receive an offer from us, our International Office will assist you with visas, accommodation and other related issues.


Semester 1

Compulsory Units (All students must register for this/these unit/s)

CCE3206*	Digital Signal Processing	5 ECTS
CCE5109	Algorithm Deployment	5 ECTS
CCE5110	Best Practice in Model Development and Training	5 ECTS
CCE5224	Digital Image Processing	5 ECTS
CCE5502	Fundamentals of AI and ML	5 ECTS
ICT5902	Research Methods	5 ECTS


Semester 2

Compulsory Units (All students must register for this/these unit/s)

ARI5121	Applied Natural Language Processing	5 ECTS
CCE5106	Deep Learning Neural Networks	5 ECTS
CCE5204	Advanced Digital Signal Processing	5 ECTS
CCE5215	Computer Vision	10 ECTS
CCE5216	Remote Sensing	5 ECTS


Summer Semester

Compulsory Units (All students must register for this/these unit/s)

CCE5901	Dissertation	30 ECTS

*Students are required to register for this study-unit or another study-unit as directed by the Board of Studies

Students who at the discretion of the board are found to be lacking in essential knowledge can be asked to follow, as part of the Elective study-units in lieu of those listed above, not more than four Level 3 study-units of which not more than 2 study-units can be outside the Faculty of ICT.The University shall make every effort to ensure that the published Course Plans, Programmes of Study and study-units catalogues are complete and up-to-date, but reserves the right to make changes on the recommendation of the relevant Board. The availability of the elective study-units may be subject to timetabling constraints. Study-units not attracting a sufficient number of registrations may be withdrawn without notice.

This programme of study is governed by the General Regulations for University Postgraduate Awards, 2021 and by the Bye-Laws for the award of the Degree of Master of Science - M.Sc. - under the auspices of the Faculty of 福利在线免费 and Communication Technology.

By the end of the course, you will be able to show:

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.

Non EU Applicants:

Total Tuition Fees: Eur 13,400

Bench fees may apply - Kindly refer to Bench Fees Indicative Charges document.

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As a graduate with a M.Sc. in Signal Processing and Machine Learning, you will 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 employment with large research groups in industry, research institutes, and universities abroad.

This degree enables also further studies leading to a doctorate degree.

Every effort has been made to provide information that is current and accurate. However, as the content is being constantly updated, users are advised to verify the details contained in these web pages with the relevant University office or authority before making decisions based on the published information.