Programme Title
Bachelor of Science (Honours) in Applied Data Sciences
Course Code

IT6-A08-23
Programme Includes:(Apprenticeship/ Placement or Internship)

Apprenticeship
MQF Level

Level 6
Type(refer to Appendix 1 for Parameters)

Qualification
Accreditation Status(Note: If the Type is Award or Qualification, therefore by default, the Accreditation Status should be Accredited)

Accredited via MCAST’s Self Accreditation Process (MCAST holds Self-Accrediting Status as per 1st schedule of Legal Notice 296/2012)
Mode of Delivery

Face to Face
Duration (hours or years)

3 Years
Total Number of Credits

180 ECTS
Total Learning Hours (25 Total Learning Hours for each ECTS)

4500 Hours
Target Audience

Ages 16 – 65
Target Group (the type of learners that the educational institution anticipates joining this programme)

Programme Fees

€19,500.00 (Applicable for Non-EU and Non-EEA Countries) – the fee mentioned here is indicative.  Please refer to www.mcast.edu.mt, as well as to MCAST’s MG2I International Section for any updated fees as well as terms of payments.
Date of Next Student Intake

2024-10-01
Language of Instruction

The official language of instruction at MCAST is English. All notes and textbooks are in English (except for language courses, which will be in the respective language being instructed). International candidates will be requested to meet English language certification requirements for access to the course.
Application Method

Applications to full-time courses are received online via the College Management Information System. Applicants can log-in using Maltese Electronic ID (eID) in order to access the MCAST Admissions Portal directly and create one’s own student account with the identity being verified electronically via this secure service.

Non-EID applicants need to request account creation though an online form after that they confirm that their local Identification Document does not come with an EID entitlement. Once the identity is verified and the account is created on behalf of the applicant, one may proceed with the online application according to the same instructions applicable to all other applicants.

For more information about how to apply online for a course at MCAST, please visit: https://mcast.edu.mt/how-to-apply-online-2/

Information for Non-EU Citizens

Non-EU candidates require a study visa in order to travel to Malta and join the course applied for. For further information re study-visa please access https://www.identitymalta.com/unit/central-visa-unit/.
Address where the Programme will be Delivered

MCAST has four campuses as follows:

MCAST Main Campus
Triq Kordin,
Paola, Malta

All courses except for courses delivered by the Institute for the Creative Arts, the Centre of Agriculture, Aquatics and Animal Sciences and the Gozo Campus are offered at the Main Campus address (above).

Courses delivered by the Institute for the Creative Arts, the Centre of Agriculture, Aquatics and Animal Sciences, or the Gozo Campus, are offered in one of the following addresses as applicable:

Institute for the Creative Arts
Mosta Campus
Misraħ Għonoq Tarġa Gap,
Mosta

Institute of Applied Sciences
Centre of Agriculture, Aquatics and Animal Sciences,
Luqa Road, Qormi

Gozo Campus
J.F. De Chambray Street
MCAST, Għajnsielem
Gozo

In the case of courses delivered via Online Learning, students will be following the programme from their preferred location/address.

Programmes delivered via Blended Learning, and which therefore contain both an online and a face to face component shall be delivered as follows:

Face to Face components – as per above address instructions
Online components – from the student’s preferred address.

Course Description/Deskrizzjoni tal-Kors

English

The degree in Applied Data Sciences is designed for individuals who are interested in utilizing data to solve complex challenges in various fields. With a focus on applied methodology, analytical skills, and hands-on experience, students will learn how to use advanced analytical tools and techniques to uncover hidden trends and patterns that can lead to business success. The programme covers a range of topics related to software engineering, data organization, and data analysis using the latest technologies in business intelligence, reporting, machine learning, and big data. In addition, the degree includes a strong emphasis on text mining and natural language processing (NLP), which are key tools for extracting insights from unstructured data.
The program also covers critical thinking skills, building strategies for promoting businesses, understanding consumer behaviour, computational linguistics and the laws governing business processes. A work-based component provides an opportunity for students to gain valuable industry experience and learn from real-world professionals. At the end of the programme, students will undertake a research component in the form of a dissertation. The degree is ideal for individuals who are passionate about leveraging technology to drive business performance and make data-driven decisions.



Malti

Il-programm fil-livell ta’ baċellerat f’Applied Data Sciene huwa mfassla għal individwi li huma interessati li jutilizzaw id-data biex isolvu sfidi kumplessi f’diversi oqsma. B’enfasi fuq metodoloġija applikata, ħiliet analitiċi, u esperjenza prattika, l-istudenti se jitgħallmu kif jużaw għodda analitiċi avvanzati biex jikxfu xejriet u mudelli li jistgħu jwasslu għas-suċċess tan-negozju. Il-programm ikopri firxa ta’ suġġetti relatati mal-inġinerija tas-software, l-organizzazzjoni tad-data u l-analiżi tad-data bl-użu tal-aħħar teknoloġija fl-intelliġenza tan-negozju, ir-rappurtar, machine learning u l-big data. Barra minn hekk, il-programm jinkludi enfasi qawwija fuq text mining u l-ipproċessar tal-lingwa naturali (NLP), li huma għodod ewlenin biex ikun hemm analiżi tad-data mhux strutturata. Il-programm ikopri wkoll ħiliet ta’ ħsieb kritiku, bini ta’ strateġiji għall-promozzjoni tan-negozji, studju dwar l-imġiba tal-konsumatur, lingwistika komputazzjonali u l-liġijiet li jirregolaw il-proċessi tan-negozju. Komponent ibbażat fuq ix-xogħol jipprovdi opportunità għall-istudenti biex jiksbu esperjenza siewja fl-industrija u jitgħallmu minn professjonisti fid-dinja tax-xogħol. Fi tmiem il-programm, l-istudenti se jagħmlu ukoll proġett tar-riċerka. Il-kors huwa ideali għal individwi li għandhom passjoni biex jużaw it-teknoloġija biex imexxu l-prestazzjoni tan-negozju u jieħdu deċiżjonijiet ibbażati fuq l-użu tad-data
Career Opportunities

Data Analyst, Business Analyst, Data Scientist, Data Engineer*, Machine Learning Engineer*, Big Data Engineer*, Data Architect, Data Mining Engineer*, Data Visualization Specialist
*The term Engineer shall not carry or imply the meaning attributed to the term “Engineer” in Article 2 of the Engineering Profession Act (Chapter 321 of the Laws of Malta)
Entry requirements(Refer to Programme Specification)

MCAST Advanced Diploma in IT
or
MCAST Advanced Diploma in Business Administration
or
MCAST Advanced Diploma in Marketing
or
MCAST Advanced Diploma in Insurance
or
MCAST Advanced Diploma in Financial Services
or
MCAST Advanced Diploma in Finance and Insurance
or
2 A-Level passes and 2 I-Level passes
Compulsory A-Level: Computing or Mathematics or Accounting or Economics or Marketing
Applicants with a good working knowledge of Computing, Mathematics and Business related subjects will benefit from a more positive learning experience throughout the course

Other entry requirements
Experience in a programming language would be considered an asset.
A sound background in the use of the English Language will be an asset for students to attain the best educational experience.

Programme Learning Outcomes (Refer to Programme Specification)

At the end of the programme the learner will be able to:

1. Acquire knowledge and skills in various areas of information technology, business, and finance.
2. Evaluate and solve problems in a diverse range of data contexts.
3. Apply theoretical knowledge to real-world situations and develop practical solutions to address business and technological challenges.
4. Develop a strong ethical and professional foundation to be able to apply ethical
principles and best practices to a variety of situations, including data governance, security, privacy, and social responsibility.

Teaching, Learning and Assessment Procedures

The programmes offered are vocational in nature and entail both theoretical lectures delivered in classes as well as practical elements that are delivered in laboratories, workshops, salons, simulators as the module requirements dictate.

Each module or unit entails a number of in person and/or online contact learning hours that are delivered by the lecturer or tutor directly (See also section ‘Total Learning Hours).

Access to all resources is provided to all registered students. These include study resources in paper or electronic format through the Library and Resource Centre as well as tools, software, equipment and machinery that are provided by the respective institutes depending on the requirements of the course or module.

Students may however be required to provide consumable material for use during practical sessions and projects unless these are explicitly provided by the College.

All Units of study are assessed throughout the academic year through continuous assessment using a variety of assessment tools. Coursework tasks are exclusively based on the Learning Outcomes and Grading Criteria as prescribed in the course specification. The Learning Outcomes and Grading Criteria are communicated to the Student via the coursework documentation.

The method of assessment shall reflect the Level, credit points (ECTS) and the schedule of time-tabled/non-timetabled hours of learning of each study unit. A variety of assessment instruments, not solely Time Constrained Assignments/Exams, are used to gather and interpret evidence of Student competence toward pre-established grading criteria that are aligned to the learning outcomes of each unit of the programme of study.

Grading criteria are assessed through a number of tasks, each task being assigned a number of marks. The number of grading criteria is included in the respective Programme Specification.
The distribution of marks and assessment mode depends on the nature and objectives of the unit in question.

Coursework shall normally be completed during the semester in which the Unit is delivered.

Time-constrained assignments may be held between 8 am and 8 pm during the delivery period of a Unit, or at the end of the semester in which the Unit is completed. The dates are notified and published on the Institute notice boards or through other means of communication.

Certain circumstances (such as but not limited to the Covid-19 pandemic) may lead Institutes and Centres to hold teaching and assessment remotely (online) as per MCAST QA Policy and Standard for Online Teaching, Learning and Assessment (Doc 020) available via link https://www.mcast.edu.mt/college-documents/

The Programme Regulations pertaining to this Programme’s MQF/EQF level available at: link https://www.mcast.edu.mt/college-documents/, apply.

Grading System

All MCAST programmes adopt a Learner-centred approach through the focus on Learning Outcomes. The assessment of MCAST programmes is criterion-referenced and thus assessors are required to assess learners’ evidence against a pre-determined set of Learning Outcomes and Assessment Criteria.

For a student to be deemed to have successfully passed a unit, a minimum of 50% (grade D) must be achieved.

All full time units are individually graded as follows:
A* (90-100)
A (80-89)
B (70-79)
C (60-69)
D (50-59)
Unsatisfactory work is graded as ‘U’.

Work-based learning units are graded on a Pass/Fail basis only.

Detailed information regarding the grading system may be found in the Programme Regulations pertaining to this programme’s MQF/EQF Level available at: link https://www.mcast.edu.mt/college-documents/

Contact details for Further Learning Opportunities

MCAST Career Guidance
Tel: 2398 7135/6
Email: career.guidance@mcast.edu.mt
Regulatory Body/ Competent Authority Contact Details (where applicable – in the case of a programme leading to Regulated Profession)

Download
Download PIT (Public Information Template) pdf here  
Download Abridged Course Spec pdf here  

Last updated: 2024-08-01