Master of Science in Artificial Intelligence [Taught and Research (Mainly by Research)]

Master of Science in Artificial Intelligence [Taught and Research (Mainly by Research)]

Course Title

Master of Science in Artificial Intelligence [Taught and Research (Mainly by Research)]

MQF Level

7

Duration and Credits

4 Semesters

90 ECTS

Mode of Study

Part-time Evening

Information for International applicants

Applicants must be in possession of:

Refer to the list of country-specific qualifications

  1. a Bachelor degree pegged at Level 6 on the Malta Qualifications Framework and obtained with at least Second Class (Honours) or Category II in ICT or an area with a strong ICT component, or in Engineering, or
  2. a Bachelor degree pegged at Level 6 on the Malta Qualifications Framework classified with Third Class Honours or Category III in the areas outlined in paragraph (a) above, provided that such applicants shall satisfy the Board of Studies that they are in possession of other qualifications, or relevant work experience, obtained following their first cycle degree. The Board of Studies may recommend to the Faculty Admissions Committee that the admission of such applicants may be made conditional on the results of an interview conducted for the purpose or
  3. 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.

Interviews, when necessary, shall be conducted by a board composed of at least three members.

Eligible applicants may register as visiting students for individual study-units and obtain credit for them. Subject to approval by the Board, credits awarded for any such study-units may be transferred to the Course, provided that not more than seven years have elapsed from the successful completion of the study-unit. When credit for more than one study-unit is being transferred to the Course, then the seven years shall commence from the date of the last credit awarded.

You are viewing the entry requirements for International applicants. Switch to Local qualifications.

Need help? Request more information

Apply

Applications for our February and October intakes have been officially open since the third week in November. 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.

The University of Malta has student accommodation on campus called Campus Hub. Campus Hub is just a 2-minute walk from the main campus. For more information, visit the accommodation website.

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.

The M.Sc. in Artificial Intelligence (AI) 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 (Astronomy, Big Data, Computer Vision, Fintech, Geosciences, Robotics, or Statistics) or simply a generic advanced AI domain, before proceeding to a dissertation. 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.

In addition to the compulsory study-units for the year (10 ECTS credits), students are required to register for 5 ECTS credits from the elective study-units on offer during Semester 1 and 15 ECTS credits from the elective study-units on offer during Semester 2. The choice of elective study-units is to be made from Computer Vision, Big Data, Robotics, Fintech and/or Geosciences Streams.

An elective stream/study-unit will ONLY be offered if a sufficient number of students register for it. Consequently, the availability of respective study-units will only be confirmed after the registration period.
 
Semester 1
 
Compulsory Units (All students must register for this/these unit/s)
 
ARI5902 Research Topics in Artificial Intelligence 5 ECTS    
ICS5110 Applied Machine Learning 5 ECTS    
 
Elective Units (Elective units are offered subject to availability, a minimum number of student registrations and time-table constraints).

Big Data Stream
 
ARI3333 Generative AI 5 ECTS    
ICS5111 Mining Large-Scale Data 5 ECTS    
 
Robotics Stream
 
ARI5905* Research Topics in Natural Language Processing 5 ECTS    
 
Fintech Stream
 
ARI5122 Financial Engineering 5 ECTS    
 
Geosciences Stream
 
ICS5111 Mining Large-Scale Data 5 ECTS    
 
Astronomy Stream
 
SSA5065 Principles of Astronomy and Cosmology 5 ECTS    

 
 
Semester 2
 
Elective Units (Elective units are offered subject to availability, a minimum number of student registrations and time-table constraints).

Astronomy Stream
 
ARI5102 Data Analysis Techniques 5 ECTS    
ARI5118 Deep Learning for Computer Vision 5 ECTS    
SSA5075 Computational Methods for Astronomy 5 ECTS    
 
Big Data Stream
 
ARI5102 Data Analysis Techniques 5 ECTS    
ARI5121 Applied Natural Language Processing 5 ECTS    
ICS5115 Statistics for Data Scientists 5 ECTS    
 
Robotics Stream
 
ARI5118 Deep Learning for Computer Vision 5 ECTS    
ARI5121 Applied Natural Language Processing 5 ECTS    
ARI5321 Automation and Applied Robotics 5 ECTS    
ICS5115 Statistics for Data Scientists 5 ECTS    
ICT5101 Internet of Things 5 ECTS    
 
Fintech Stream
 
ARI5123 Intelligent Algorithmic Trading 5 ECTS    
ICS5115 Statistics for Data Scientists 5 ECTS    
 
Geosciences Stream
 
GSC5300 Big Data in Geosciences 5 ECTS    
ICS5115 Statistics for Data Scientists 5 ECTS    
 
Computer Vision Stream
 
ARI5118 Deep Learning for Computer Vision 5 ECTS    

 
* This study-units will be offered as directed by the Board of Studies only.

 
Year   (This/these unit/s start/s in Semester 1 and continue/s in Semester 2)
 
Compulsory Units (All students must register for this/these unit/s)
 
ICS5200 Dissertation 60 ECTS    

 

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 Information and Communication Technology.

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

  • Apply your previous knowledge from your undergraduate degree to applied intelligence computer systems.
  • Gain insightful and practical knowledge that will later apply to specific focuses like Big Data Analytics, Computer Vision, Robotics and Fintech.
  • Analyse and critically evaluate applicability of both machine learning, statistical and data mining approaches.
  • Develop the capacity to analyse and critically evaluate applicability of Computer Vision algorithms for given problems.
  • Understand the technologies used by a machine to understand, process and generate language.
  • Analyse and critically evaluate applicability of Computational Finance algorithms for given problems.
  • Develop and apply artificial intelligence algorithms for the data deluge emanating from large astronomical instruments.

The core first part of the M.Sc. in AI ensures that you will:

  1. Be able apply your previous knowledge from your 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 and automation.
  4. Acquire basic skills that will help you through the second part of the course but also to employ them in everyday life involving big data, creative technologies, artificial vision and automation.
In the second part of the course you can focus on four distinct research domains that each carries a specific programme rational and learning outcomes.

The Big Data 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 largescale 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 the big data stream are:

  1. A highly analytical approach to problem solving;
  2. Ability to extract value and insight from data;
  3. Ability to analyse and critically evaluate applicability of both machine learning, statistical and data mining approaches;
  4. 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.

You will:

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

The Artificial Vision stream focuses on the state ֯f-the-art techniques that extract information from images and videos. Artificial vision is proving to be crucial in various industrial applications, such as manufacturing (e.g. Visual quality inspection), entertainment (e.g. Capture body movement with Kinect sensor), robotics (e.g. Exploring a new place), health (e.g. Medical image processing), and security (e.g. Pedestrian and car tracking), among others. The need for further development of artificial vision is increasing exponentially and so are the career opportunities.

You will:

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

The Artificial Vision stream focuses on the state ֯f-the-art techniques that extract information from images and videos. Artificial vision is proving to be crucial in various industrial applications, such as manufacturing (e.g. Visual quality inspection), entertainment (e.g. Capture body movement with Kinect sensor), robotics (e.g. Exploring a new place), health (e.g. Medical image processing), and security (e.g. Pedestrian and car tracking), among others. The need for further development of artificial vision is increasing exponentially and so are the career opportunities.

You will:

  1. Gain broad knowledge on various state ֯f the-art algorithms.
  2. Understand how the visual system of the brain processes visual information.
  3. Understand the challenges of artificial vision algorithms in real-world applications.
  4. Develop hands on experience in the implementation of various algorithms using Matlab/Python.
  5. Develop the ability to analyse and critically evaluate applicability of artificial vision algorithms for given problems.
  6. Be prepared for a career in the vision-based industries.
  7. 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.

Learning outcomes from the Automation stream are:

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

Non EU Applicants:

Total Tuition Fees: Eur 13,400
Yr 1: Eur 6,700 - Yr 2: Eur 6,700

Bench fees may apply - Kindly refer to 'Bench Fees Indicative Charges' document available here

You are viewing the fees for non EU nationals. Switch to EU nationals if you are a national of any country from within the EU/EEA.

On successfully completing the M.Sc. in AI, you will be able to further pursue your studies towards a Ph.D. or apply your acquired knowledge of your line of work by fruitfully applying either big data analytics, computer vision, robotics or computational finance to your line of work. Alternatively, new possibilities to switch to a fresh career within these four 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 streams being offered.

Technology Stream

 

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.

Hello there. We noticed that you are searching from an overseas country. Do you possess any overseas qualifications?

Hello there. We noticed that you are searching from outside the European Union.

Are you an EU/EEA national?

https://www.um.edu.mt/courses/overview/pmsciaripet7-2024-5-o/