PMSCIIIDTCPET2-2024-5-O - L-Università ta' Malta

Course Title

Master of Science in Data Science

MQF Level

Duration and Credits

6 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

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
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
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.

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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.

Managing and analysing Big Data has become an essential part of modern finance, retail, marketing, social science, research and development, medicine, industry, academia, and government. The curriculum is therefore designed to provide you with a solid grounding in the theory as well as the methods and techniques used in data science. From the onset, the industry stakeholders insisted on exposure to the basic 'core' theory in data science including discrete and continuous mathematical concepts, statistics, probability, and the theoretical foundations of machine learning and data analytics. This will ensure that, upon completion of the 60 ECTS taught component, you will have a solid background in the theory that is considered a pre-requisite for data science practitioners.


Semester 1

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

CIS5223	Concepts, Techniques and Practical Aspects of Scientific Research	5 ECTS
ICS5110	Applied Machine Learning	5 ECTS
SOR1510*	Foundations in Probability, Sampling and Estimation	5 ECTS


Semester 2

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

ARI5102	Data Analysis Techniques	5 ECTS
MAT1802*	Mathematics for Engineers 2	4 ECTS
SCI5020*	Principles of Statistical Inference	5 ECTS

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


Semester 1

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

CCE5108	Data Science in Python	5 ECTS
CIS5113	Large Scale Databases	5 ECTS
ICS5111	Mining Large-Scale Data	5 ECTS


Semester 2

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

CCE5106	Advanced Neural Network Models	5 ECTS
CIS5230	Data Analytics on the Cloud	5 ECTS
CIS5231	Topics in Applied Data Science	6 ECTS


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)

ICT5012	Dissertation	30 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 in Data 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:

Identify, describe, and apply, the theoretical concepts to find, or create, solutions to problems in data science;
Manage and organise data collection;able to show:
Analyse the data science problem and select the appropriate tools to apply;able to show:
Interpret, and relate, the results obtained from the data analytics tools;able to show:
Choose, or construct machine learning models and fit these models to real datasets and correctly interpret the results; andable to show:
Assess the validity of predictive models and their associated limitations;

Non EU Applicants:

Total Tuition Fees: Eur 13,400
Yr 1: Eur 6,700 - Yr 2: Eur 6,700 - Yr 3: NIL

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.

As a graduate in data science, you may find yourself in a variety of environments within academia, research, industry, government and private organisations. The following is a short list of possible research and vocational areas for data science graduates:

Machine Learning Specialist

Machine learning specialists create data funnels and deliver software solutions. In addition to designing and building machine learning systems, they are also responsible for running tests and experiments to monitor the performance and functionality of such systems.

Data Architect

Data architects ensure data solutions are built for performance and design analytics applications for multiple platforms. In addition to creating new database systems, data architects often find ways to improve the performance and functionality of existing systems, as well as working to provide access to database administrators and analysts.

Data Engineer

Data engineers perform batch processing or real-time processing on gathered and stored data. Data engineers are also responsible for building and maintaining data pipelines which create a robust and interconnected data ecosystem within an organization, making information accessible for data scientists.

Data Analyst

Data analysts transform and manipulate large data sets to suit the desired analysis for companies. For many companies, this role can also include tracking web analytics and analysing A/B testing. Data analysts also aid in the decision-making process by preparing reports for organizational leaders which effectively communicate trends and insights gleaned from their analysis.

With a diverse skill set in data science, you may choose to join a leading data or technology company. Alternatively, you would be perfectly equipped to drive growth in an up-and-coming enterprise or even found your own company.

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.