Duration
18 months full-time / 36 months part-time
Mode
Face-to-face
Next start date
January /April / July / October
Graduates of the Master of Science (MSc) in Computer Science (Data Science and Artificial Intelligence) program will develop a deep understanding of the fundamental concepts and principles of AI, including machine learning, deep learning, natural language processing, computer vision, and reinforcement learning. Upon completion of the program, students will be able to design and implement AI systems, using a range of programming languages, software development methodologies, and tools. Students will develop the ability to evaluate the performance of AI systems and to use a variety of techniques to improve their performance, such as data pre-processing, feature extraction, model selection, and hyper-parameter tuning. Students will become familiar with ethical, social and professional issues in AI, such as bias, privacy, transparency and explainability, and be able to navigate them and make informed decisions in their professional practice. Finally, students will have the ability to conduct original research in AI, and to contribute to the advancement of the field through publications, presentations, and other forms of scholarly communication.
18 months full-time / 36 months part-time
Face-to-face
23, Vincenzo Dimech Street, Floriana, Malta
English language
will allow learners with different learning styles and abilities to complete the programme successfully. Students will also have to prepare individual and team reports and presentations, apart from written and multiple-choice examinations. Most modules have a heavy assignment component which vary from term papers to implementing algorithms stemming from the unit.
For pass marks, grading and resist systems please refer to the Grading System at the end of the document. In specific reference to the situation where a student fails a module, they will be given one chance to resit, and if they fail the resit too, they will need to redo the module.
Malta Further & Higher Education Authority
90 Credits
Higher Education Programme
Semester 1:
Semesters 2 & 3 (Students need to then choose between the following modules, adding up to 32 ECTS):
Semester 4:
Students who have no training in the field must have completed a bachelor’s in Computer Science, Information technology or in a STEM subject. This applies to students applying for the MSc program, the Post-graduate certificate, the Post-graduate diploma and the awards.
Students without the required background may be allowed to join the course depending on the students’ circumstances and background (2 to 5 years of industry experience may also be considered). Please find our RPL policy as authorised by the MFHEA at the end of the document.
A good grasp of scientific English is also required in order to follow the course. Students will be asked to provide an IELTS certificate higher than grade 7 (or equivalent) or proof of an equivalent level of English before commencing the course if the student has not followed their BSc in a primarily English-speaking country.
Candidates will be asked to present their previously obtained qualifications along with their respective transcripts.
The courses outlined below all stem from the main track (Master of Science (MSc) in Computer Science) –
Master of Science (MSc) in Computer Science (Data Science and Artificial Intelligence)
The Artificial Intelligence track is an advanced research-led course in the field of Data Science and Artificial intelligence, developing students’ skills in logic, language processing and machine learning applied to various problem domains in research and industry.
Object Oriented Modelling –Â 200 (Contact Hours : 40 | Self-Study : 58 | Supervised, Placement and Tutorials : 2 | Assessment : 100).
Research Methods in Computer Science –Â 150 (Contact Hours : 30 | Self-Study : 68 | Supervised, Placement and Tutorials : 2 | Assessment : 50).
Introduction to Artificial Intelligence –Â 300 (Contact Hours : 60 | Self-Study : 158 | Supervised, Placement and Tutorials : 0 | Assessment : 80).
Final Project –Â 500 (Contact Hours : 100 | Self-Study : 250 | Supervised, Placement and Tutorials : 10 | Assessment : 140).
Practicuum –Â 500 (Contact Hours : 5 | Self-Study : 235 | Practicuum : 240 | Assessment : 20).
Applied Artificial Intelligence –Â 500 (Contact Hours : 5 | Self-Study : 235 | Practicuum : 240 | Assessment : 20).
– Students need to then choose a few of the following modules, adding up to 32 ECTS:
Ability to conduct research and contribute to the advancement of AI: Graduates should have the ability to conduct original research in AI, and to contribute to the advancement of the field through publications, presentations, and other forms of scholarly communication.
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