Bachelor of Science in Information Technology (Honours) (Artificial Intelligence)

Bachelor of Science in Information Technology (Honours) (Artificial Intelligence)

Course Title

Bachelor of Science in Information Technology (Honours) (Artificial Intelligence)

MQF Level

6

Duration and Credits

3 Years

180 ECTS

Mode of Study

Full-time

Information for International applicants

Two passes at Grade C or better in Pure Mathematics and Computing provided that one of these passes is at Advanced Level and the other pass is at least at Intermediate Level.

Admission to this course is also open to applicants in possession of the Certificate in ICT Foundation Studies from the University of Malta.

Admission to this course is also open to applicants in possession of:

  1. an Advanced Level pass at Grade C or better in Pure Mathematics, or at a corresponding level of other examinations recognised by Senate for the purpose of the Admissions Regulations and
  2. either the Diploma of the City and Guilds of London Institute Course No.7235 in Applied Information Technology or the MCAST-BTEC Extended Diploma in IT or the MCAST Advanced Diploma in IT or the MCAST-BTEC Higher National Diploma (HND) in Computing.

Applicants wishing to join the part-time mode must submit their application as full-time, and then include a note in the comments box of the online application, denoting their preference to be considered for the part-time option. Such requests will be considered by the Faculty Board.

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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.

Applicants wishing to join the part-time mode must submit their application as full-time, and then include a note in the comments box of the application form, denoting their preference to be considered for the part-time option. Such requests will be considered by the Board of the Faculty.

The degree has three main objectives:

i)to provide coverage of the fundamental topics in computer science necessary to appreciate Artificial Intelligence;

ii)coverage of essential skills and knowledge required in the ICT industry at large;

iii)for you to acquire the unique ability to look at the world in a different way to identify and leverage opportunities for industries to increase their competitiveness in the Knowledge Age.

The degree is suitable if you are interested in designing and building intelligent computational systems in areas related to knowledge management; natural language processing; game AI; Web intelligence; systems that are able to learn; systems that are able to adapt to the needs, interests, preferences, and requirements of their users; systems that are able operate autonomously to communicate and collaborate with each other to solve real-world problems; and advanced user interfaces that enable progressive human-computer interaction.

Communication and Academic Skills Programme

The communication and academic skills programme complements students’ main course of study. It introduces them to writing and presenting as situated within academic contexts sensitive to specific disciplines and develops their competences for future careers.

 
Semester 1
 
Compulsory Units (All students must register for this/these unit/s)
 
ARI1101 Foundations of Data Science 5 ECTS    
ARI1102 Programming for AI 5 ECTS    
ARI1103 AI Numerical Methods 1 5 ECTS    
CPS1002 Mathematics of Discrete Structures 5 ECTS    
CPS1011 Programming Principles in C 5 ECTS    
ICS1020 Foundations of Artificial Intelligence 5 ECTS    

 
 
Semester 2
 
Compulsory Units (All students must register for this/these unit/s)
 
ARI1104 Foundations for Data Science 2 5 ECTS    
ARI1204 AI Numerical Methods 2 5 ECTS    
CIS1043 Introduction to Databases and Information Management 5 ECTS    
CPS1014 Operating Systems 5 ECTS    
ICS1019 Knowledge Representation and Reasoning 5 ECTS    
ICT1018 Data Structures and Algorithms 5 ECTS    

 
Requirement for regular progression to Year II: 60 ECTS credits

Students are required to register for ALL compulsory study-units (35 ECTS credits) and 25 ECTS credits from the elective study-units on offer during the year, for a total of 60 ECTS credits.
 
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)
 
ICS2000 Group Assigned Practical Task 5 ECTS    

 
 
Semester 1
 
Compulsory Units (All students must register for this/these unit/s)
 
CPS2004 Object Oriented Programming 5 ECTS    
CPS2005 Formal Languages and Automata 5 ECTS    
ICS2207 Machine Learning: Introduction to Classification, Search and Optimisation 5 ECTS    
 
Elective Units (Elective units are offered subject to availability, a minimum number of student registrations and time-table constraints)
 
ARI2101 Fundamentals of Automated Planning 5 ECTS    
ARI2131 Artificial Intelligence in Education (AIED) 5 ECTS    
ARI2205 Interpretable Artificial Intelligence 5 ECTS    
ICS2203 Statistical Natural Language Processing 5 ECTS    
ICS2205 Web Intelligence 5 ECTS    
ICS2211 Game AI 5 ECTS    

 
 
Semester 2
 
Compulsory Units (All students must register for this/these unit/s)
 
ARI2201 Individual Assigned Practical Task 5 ECTS    
CPS2000 Compiler Theory and Practice 5 ECTS    
ICS2210 Data Structures and Algorithms 2 5 ECTS    
 
Elective Units (Elective units are offered subject to availability, a minimum number of student registrations and time-table constraints)
 
ARI2129 Principles of Computer Vision for AI 5 ECTS    
ARI2202 Robotics 1 5 ECTS    
ARI2204 Reinforcement Learning 5 ECTS    
ARI2571 Computational Morphology and Syntax 5 ECTS    
ICS2208 Intelligent Interfaces 1 5 ECTS    

 
Requirement for regular progression to Year III: 60 ECTS credits

Students are required to register for ALL compulsory study-units (30 ECTS credits) and 30 ECTS credits from the elective study-units on offer during the year, for a total of 60 ECTS credits.
 
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)
 
ICT3909 Final Year Project in Artificial Intelligence 30 ECTS   (NC)  

 
 
Semester 1
 
Compulsory Units (All students must register for this/these unit/s)
 
ICS3206 Machine Learning, Expert Systems and Fuzzy Logic 5 ECTS    
 
Elective Units (Elective units are offered subject to availability, a minimum number of student registrations and time-table constraints)
 
ARI3129 Advanced Computer Vision for Artificial Intelligence 5 ECTS    
ARI3205 Interpretable AI for Deep Learning Models 5 ECTS    
ARI3210 Speech Technology 5 ECTS    
ARI3212 Advanced Reinforcement Learning 5 ECTS    
ARI3215 Robotics 2 5 ECTS    
ARI3216 Web Data Mining 5 ECTS    
ARI3333 Generative AI 5 ECTS    
ARI3900 Ethics and Artificial Intelligence 5 ECTS    
ICS3209 Advanced Game AI 5 ECTS    
ICS3211 Intelligent Interfaces 5 ECTS    
LLT3511 Deep Learning Approaches to Natural Language Processing 5 ECTS    

 


Requirement for successful completion of Year III: 60 ECTS credits.

Requirement for award of Bachelor of Science in Information Technology (Honours) (Artificial Intelligence): 180 ECTS credits.

This programme of study is governed by the General Regulations for University Undergraduate Awards, 2019 and and by the Bye-Laws for the award of the Bachelor of Science in Information Technology (Honours) – B.Sc. IT (Hons) – under the auspices of the Faculty of Information and Communication Technology.

During the course, you will learn and demonstrate your intellectual skills and transferrable practical skills by:

  • Investigating prior work in the domain and comparing previous approaches to identify relevant solutions.
  • Specifying why and how prior work is relevant and applying it to a chosen or given problem.
  • Planning and organising research-based and design and implementation-oriented tasks, and writing a critical analysis of the prior work and a justified approach to their solution in a scientific and mature manner.
  • Assessing possible approaches to evaluation, justifying the chosen approach, carrying out the chosen evaluation, and describe the evaluation.
  • Using the correct tools and AI techniques to solve different problems in different contexts.
  • Applying general and personal skills in relation to report writing and presentations.
  • As a graduate, you will be able to identify, leverage, and grasp opportunities to apply AI techniques to solve real-world problems and to engage in the study of AI. You will be expected to cope with key challenges in computing such as how to perceive the environment, represent human knowledge, use computational models to understand, explain and predict complex behaviour of individuals, groups, and systems, and make computational devices as natural to interact with as people.

    The compulsory study-units in the programme of study will give you the background in Computer Science and Artificial Intelligence. If you perform well in examinations and assignments, you will be able to grasp advanced concepts in Artificial Intelligence and can demonstrate your knowledge and understanding of these concepts by satisfying the requirements of the advanced study-units. In particular, you will be able to identify opportunities for applying AI techniques to solve real-world problems; recognise when the use of AI techniques to solve problems is beneficial; design and implement solutions; justify your approach; identify how your solution should be evaluated and carry out the evaluation. The Final Year Project gives you the opportunity to show-case your ability to independently carry out research, apply your knowledge and understanding to analyse and solve or partially solve a problem using AI techniques, clearly describe and justify your approach in a scientific and mature manner, and demonstrate the ability to recognise the contribution you have made by drawing appropriate conclusions based on the success of their approach.

    Artificial Intelligence is an intellectually challenging area of study. To be successful, you must not only demonstrate an understanding of fundamentals of Computer Science, but must be able to devise heuristics and partial solutions to build systems that are capable of solving problems that traditionally require human "intelligence" to solve. Students must be creative and innovative to identify problems that are worth solving - and these opportunities are increasing as more information is made available via the WWW, and computational devices become increasingly capable of using data and information from the environment around us, and are increasingly used to modify our perspective of, or to enable us to better interact with, the environment around us - and to identify and reason about solutions that can be demonstrated to work or to support human activities.

    You will demonstrate their intellectual skills by:

    • Investigating prior work in the domain and comparing previous approaches to identify relevant solutions.
    • Specifying why and how prior work is relevant and applying it to a chosen or given problem.
    • Planning and organising research-based and design and implementation oriented tasks, and writing a critical analysis of the prior work and a justified approach to their solution in a scientific and mature manner.
    • Assessing possible approaches to evaluation, justifying the chosen approach, carrying out the chosen evaluation, and describe the evaluation.
    • Analysing the results of the evaluation to demonstrate the success of their solution, or if it fails, to explain the failure and how their approach could be improved.
    • Judging their work objectively by drawing logical and appropriate conclusions that are consistent with the prior work, chosen approach, evaluation results and analysis of the results obtained.

    You will demonstrate their key/transferable and professional and practical skills by:

    • Using the correct tools and materials to presents different aspects of their work.
    • Using the correct tools and AI techniques to solve different problems in different contexts.
    • Applying general and personal skills in relation to report writing and presentations.
    • Carrying out research, analysis, design, implementation, and evaluation independently.
    • Solving problems in a justifiable and appropriate manner; Working as part of a team. Applying ethical approaches.

    Non EU Applicants:

    Fee per academic year: Eur 10,800

    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.

    The programme of studies will ensure that you will be employable in a variety of IT-related jobs by ensuring that you acquire C and Java programming, database, and mathematical skills, knowledge, and competencies. You will bring to industry AI skills, knowledge, and competencies in Web Intelligence, Natural Language Processing, Knowledge Acquisition, Representation, Reasoning, and Management (Knowledge Systems Development), Game Development, Deep Learning, Robotics and User Adaptive Systems. Working as part of a team, you will have the ability to see opportunities for integrating "intelligence" into mainstream IT systems.

    Through this degree programme, we will prepare you to undertake research in AI at postgraduate level at the University.

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