Computer Science
(BSc, 4 Years)
Duration
4 years
Qualification Awarded
BSc in Computer Science
Level of Qualification
Bachelor Degree (1st Cycle)
Language of Instruction
English
Mode of Study
Full-time or Part-time
Minimum ECTs Credits
240
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Computer Science (BSc, 4 Years)
| Duration | 4 years |
| Qualification Awarded | BSc in Computer Science |
| Level of Qualification | Bachelor Degree (1st Cycle) |
| Language of Instruction | English. |
| Mode of Study | Full-time or Part-time |
| Minimum ECTS Credits | 240 ECTS |
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Profile of the programme
The program aims to provide students with a solid foundation in the field of computer science while preparing them to excel as professionals in an AI-driven era.
The program has been designed around a core of computer technology foundations and principles, problem-solving and algorithmic thinking, systematic program development and testing, and modern approaches to systems analysis and software design. The curriculum is enriched with specialized topics on cutting-edge technologies, including, machine learning, big data, cloud computing, generative AI, ethical hacking and network defense, and IoT, ensuring that students gain the skills and knowledge required to design and develop complex, intelligent software systems. Emphasis is placed on applying these modern technologies to create innovative, scalable, and ethical solutions that address the evolving needs of a highly connected society.
The main aims of the program are:
- Provide students with advanced theoretical and practical knowledge in computer science, enabling them to excel in the IT environments of commercial, industrial, and governmental sectors.
- Equip students with the skills and adaptability needed to thrive in an era of rapid technological advancement, particularly in fields influenced by AI and machine learning.
- Prepare students for further postgraduate education, research, and innovation in cutting-edge domains such as AI, IoT, and cybersecurity.
- Foster a strong sense of ethical responsibility, social commitment, global vision, and independent self-learning abilities to address challenges in an increasingly interconnected and AI-driven world.
- Encourage creativity and innovation in developing scalable and sustainable solutions that align with societal and environmental needs.
The BSc in Computer Science exposes students to current and emerging trends, preparing them for a wide range of computer-related professions such as research, development, management, and teaching, in a rapidly growing field that deeply impacts modern societies and economies. Graduates have the opportunity to pursue various career paths and work in a wide spectrum of professions and sectors, including Technology & IT, Cybersecurity, Financial Sector, Health & Biomedicine, Industry & Energy, Retail & Marketing, Public Sector & Policy Analysis.
Occupational Profiles of Graduates with Examples
The degree in Computer Science offers students the opportunity to explore multiple career opportunities in a wide range of fields such as:
- Technology & IT
Big Tech companies, startups, software development firms: Engaging in the design, development, and optimization of software and systems, as well as solving infrastructure issues.
- Cybersecurity
Security companies, government organizations, and private enterprises: Developing security strategies, monitoring network infrastructures for threats, and developing solutions for data protection.
- Financial Sector
Banks, FinTech companies: Developing secure banking applications, transaction systems, and facilitating processes through automation and blockchain technology.
- Health & Biomedical
Pharmaceutical companies, hospitals: Creating software for medical applications, patient management systems, and supporting research and development of new health technologies.
- Industry & Energy
Management of IoT and Smart Grids: Developing and integrating systems for automated processes and improving energy efficiency through advanced IT infrastructures.
- Retail & Marketing
E-commerce platforms, content management systems, and optimizing user experience through the development of online and mobile applications.
- Public Sector & Policy Analysis
Developing and managing IT systems for government services, with an emphasis on data security and process automation.
Access to Further Studies
Graduates of the programme can be accepted into Second Cycle degrees (Master’s Degree)
Admission Criteria
Academic Admission
The minimum admission requirement to an undergraduate programme of study is a recognized High School Leaving Certificate (HSLC) or equivalent internationally recognized qualification(s). Students with a lower HSLC grade than 7.5/10 or 15/20 or equivalent depending on the grading system of the country issuing the HSLC are provided with extra academic guidance and monitoring during the first year of their studies.
English Language Proficiency
The list below provides the minimum English Language Requirements (ELR) for enrollment to the programme of study. Students who do not possess any of the qualifications or stipulated grades listed below and hold IELTS with 4.5 and above, are required to take UNIC’s NEPTON English Placement Test (with no charge) and will receive English Language support classes.
- IELTS – 6 and above
- Anglia Examinations – Advanced and above
- Cambridge GCE AS Level English Language – C and above
- Cambridge GCE English A Levels – C and above
- Cambridge IGCSE or GCSE English as a First language – C and above
- Cambridge IGCSE or GCSE English as a Second language – B and above
- IB English A: Literature SL & HL – 4 and above
- IB English Standard Level (SL) – 5 and above
- IB English High Level (HL) – 4 and above
- Michigan Language Assessment (also known as Proficiency of Michigan) – 650 and above
- Password Test – 6 and above
- TOEFL (IBT) – 60 and above
- Cambridge Exams (First Certificate) – 160 and above or Pass
- Cambridge Exams (Proficiency Certificate) – 180 and above or Pass
Course assessment usually comprises of a comprehensive final exam and continuous assessment. Continuous assessment can include amongst others, mid-terms, projects and class participation.
Letter grades are calculated based on the weight of the final exam and the continuous assessment and the actual numerical marks obtained in these two assessment components. Based on the course grades the student’s semester grade point average (GPA) and cumulative point average (CPA) are calculated.
The student must complete 240 ECTS and all programme requirements.
A minimum cumulative grade point average (CPA) of 2.0 is required. Thus, although a ‘D-‘ is a PASS grade, in order to achieve a CPA of 2.0 an average grade of ‘C’ is required.
Upon successful completion of this program, the students should be able to:
- Apply knowledge of computer science and modern technologies to model, design, and develop computer-based algorithms, systems, processes, and programs, demonstrating an understanding of the trade-offs inherent in design decisions, particularly in a decentralized and AI-driven context.
- Identify, analyze, and define criteria and specifications for solving complex computational problems, using structured strategies and advanced tools for innovative and efficient solutions.
- Demonstrate computational thinking skills by recognizing its applicability across various domains and effectively applying these skills in real-world and interdisciplinary scenarios.
- Assess and evaluate computer-based systems, processes, and programs against defined criteria, including scalability, security, and adaptability to future technological trends.
- Utilize theoretical knowledge and practical skills to specify, design, implement, and maintain intelligent systems, integrating technologies such as generative AI, IoT, and machine learning into computing solutions.
- Evaluate and address social, professional, legal, and ethical considerations in the design, deployment, and use of computer technologies, ensuring responsible AI practices and respect for diversity and inclusivity.
- Plan, manage, and implement software projects by specifying requirements, creating solutions, and leading or collaborating effectively within development teams.
- Evaluate and optimize systems based on quality attributes, including usability, performance, security, and sustainability, while addressing trade-offs in various scenarios.
- Apply principles of data management, organization, and analysis to design and optimize database systems, particularly those relevant to big data and AI applications.
- Incorporate principles of human-computer interaction (HCI) to design and evaluate user interfaces, web pages, multimedia systems, and mobile systems, ensuring accessibility and user-centric design.
- Identify and address risks, safety, and security concerns in computer systems, emphasizing privacy, cybersecurity, and ethical considerations in an interconnected world.
- Effectively utilize modern software development tools and platforms, including open-source resources and cloud-based systems, to solve practical problems and innovate in software creation and documentation.
- Engage in collaborative, open-source projects, understanding their value in fostering innovation, inclusivity, and global contributions to the software community.
- Work effectively as part of interdisciplinary teams to design, implement, and deploy innovative solutions that integrate technologies such as generative AI, machine learning, and IoT.
- Demonstrate awareness of emerging trends and technologies in computer science, applying lifelong learning strategies to adapt to a rapidly evolving field.
Section: A Major Requirements
ECTS: Min. 126 Max. 126
| Course ID | Course Title | ECTS Credits |
|---|---|---|
| COMP-111 | Programming Principles I | 6 |
| COMP-113 | Programming Principles II | 6 |
| COMP-117 | Software Development Essentials | 6 |
| COMP-119 | Collaborative Software Development | 6 |
| COMP-200 | Digital Systems | 6 |
| COMP-201 | Systems Analysis and Design | 6 |
| COMP-212 | Object-Oriented Programming | 6 |
| COMP-221 | Advanced Programming and Paradigms | 6 |
| COMP-244 | Machine Learning and Data Mining I | 6 |
| COMP-270 | Data Structures and Algorithms | 6 |
| COMP-302 | Database Management Systems | 6 |
| COMP-321 | Theory of Computation | 6 |
| COMP-335 | Computer Organization and Architecture | 6 |
| COMP-354 | Operating Systems | 6 |
| COMP-358 | Networks and Data Communication | 6 |
| COMP-401 | Software Engineering | 6 |
| COMP-405 | Artificial Intelligence | 6 |
| COMP-417 | Parallel and Distributed Computing | 6 |
| COMP-431 | Computer Security | 6 |
| COMP-498 | Final Year Project I | 6 |
| COMP-499 | Final Year Project II | 6 |
Section: B Major Electives
ECTS: Min. 36 Max. 60
Notes: Students following a specific Thematic Area, will need to take a minimum of three courses from the respective area as follows:
- Thematic Area 1 – Artificial Intelligence and Machine Learning: COMP-340, COMP-345,
COMP-447, COMP-476 - Thematic Area 2 – Cybersecurity and Privacy: COMP-230, COMP-242, COMP-432,
COMP-433, COMP-434 - Thematic Area 3 – Internet of Things: COMP-289, COMP-470, COMP-474, COMP-475
- Thematic Area 4 – Virtual Reality and Game Development: COMP-263, COMP-320,
COMP-386, COMP-410
| Course ID | Course Title | ECTS Credits |
|---|---|---|
| COMP-213 | Visual Programming | 6 |
| COMP-230 | Cybersecurity Governance | 6 |
| COMP-242 | Data Privacy and Ethics | 6 |
| COMP-263 | Human Computer Interaction | 6 |
| COMP-289 | Web and Mobile Development | 6 |
| COMP-320 | Computer Graphics | 6 |
| COMP-340 | Big Data | 6 |
| COMP-345 | Robot Programming | 6 |
| COMP-386 | Game Programming | 6 |
| COMP-387 | Blockchain Programming | 6 |
| COMP-399C | Special Topics in Computer Science | 6 |
| COMP-410 | Virtual Reality Game Development | 6 |
| COMP-421 | Compiler Design | 6 |
| COMP-432 | Network Security | 6 |
| COMP-433 | Ethical Hacking | 6 |
| COMP-434 | Secure Systems Programming | 6 |
| COMP-447 | Neural Networks and Deep Learning | 6 |
| COMP-470 | Internet Technologies | 6 |
| COMP-474 | Cloud Computing | 6 |
| COMP-475 | Internet of Things and Wearable Technologies | 6 |
| COMP-492 | Industry Placement | 6 |
Section: C Math, Science and Engineering Electives
ECTS: Min. 30 Max. 60
| Course ID | Course Title | ECTS Credits |
|---|---|---|
| BIOL-110 | Elements of Biology | 6 |
| CHEM-105 | General Chemistry | 6 |
| ECE-100 | Electric Circuits I | 6 |
| ECE-210 | Electronics I | 6 |
| MATH-111 | Mathematics and Logic for Computation | 6 |
| MATH-195 | Calculus I | 6 |
| MATH-196 | Calculus II | 6 |
| MATH-225 | Probability and Statistics I | 6 |
| MATH-276 | Calculus III | 6 |
| MATH-280 | Linear Algebra I | 6 |
| MATH-330 | Ordinary Differential Equations | 6 |
| PHYS-110 | Elements of Physics | 6 |
Section: D Business Electives
ECTS: Min. 6 Max. 24
| Course ID | Course Title | ECTS Credits |
|---|---|---|
| ACCT-110 | Accounting I | 6 |
| BADM-234 | Organizational Behavior | 6 |
| ECON-261 | Principles of Microeconomics | 6 |
| MGT-281 | Introduction to Management | 6 |
| MGT-340 | Business Sustainability | 6 |
| MGT-370 | Management of Innovation and Technology | 6 |
| MIS-215 | Project Management | 6 |
| MIS-303 | Database Applications Development | 6 |
| MIS-351 | Information Systems Concepts | 6 |
| MIS-390 | E-Business | 6 |
| MIS-450 | Digital Transformation Management | 6 |
| MIS-456 | Management of Information Systems | 6 |
| MKTG-291 | Marketing | 6 |
Section: E Language Expression
ECTS: Min. 12 Max. 30
Notes: Placement in the English courses is done on the basis of a Placement Test or tests such
as TOEFL or GCE.
| Course ID | Course Title | ECTS Credits |
|---|---|---|
| BADM-231 | Business Communications | 6 |
| BADM-332 | Technical Writing and Research | 6 |
| BENG-100 | College English | 6 |
| COMM-200 | Business and Professional Communication | 6 |
| ENGL-100 | Basic Writing | 6 |
| ENGL-101 | English Composition | 6 |
Section: F Liberal Arts Electives
ECTS: Min. 6 Max. 24
| Course ID | Course Title | ECTS Credits |
|---|---|---|
| FREN-101 | French Language and Culture I | 6 |
| GERM-101 | German Language and Culture I | 6 |
| GREK-101 | Greek Language and Culture I | 6 |
| ITAL-101 | Italian Language and Culture I | 6 |
| MULT-160 | Introduction to Multimedia | 6 |
| PHIL-101 | Introduction to Philosophy | 6 |
| PHIL-120 | Ethics | 6 |
| PSY-110 | General Psychology I | 6 |
| PSY-111 | General Psychology II | 6 |
| SOC-101 | Principles of Sociology | 6 |
| SPAN-101 | Spanish Language and Culture I | 6 |
Section: G Unallocated Courses
ECTS: Min. 0 Max. 0
Semester 1
| Course ID | Course Title | ECTS Credits | Lecturer |
|---|---|---|---|
| COMP-111 | Programming Principles I | 6 | Andreas Savva |
| COMP-117 | Software Development Essentials | 6 | Demetris Trihinas |
| MATH-111 | Mathematics and Logic for Computation | 6 | George Chailos |
| MATH-195 | Calculus I | 6 | George Portides |
| ENGL-101 | English Composition | 6 | Aretousa Giannakou |
Semester 2
| Course ID | Course Title | ECTS Credits | Lecturer |
|---|---|---|---|
| COMP-113 | Programming Principles II | 6 | Athena Stassopoulou |
| COMP-119 | Collaborative Software Development | 6 | Harald Gjermundrød |
| MATH-196 | Calculus II | 6 | Nectarios Papanicolaou |
| BADM-234 | Organizational Behavior | 6 | |
| SOC-101 | Principles of Sociology | 6 |
Semester 3
| Course ID | Course Title | ECTS Credits | Lecturer |
|---|---|---|---|
| COMP-200 | Digital Systems | 6 | Stelios Neophytou |
| COMP-201 | Systems Analysis and Design | 6 | Vasso Stylianou |
| COMP-212 | Object-Oriented Programming | 6 | Constandinos Mavromoustakis |
| COMP-221 | Advanced Programming and Paradigms | 6 | Andreas Savva |
| COMP-213 | Visual Programming | 6 |
Semester 4
| Course ID | Course Title | ECTS Credits | Lecturer |
|---|---|---|---|
| COMP-244 | Machine Learning and Data Mining I | 6 | Ioannis Katakis |
| COMP-270 | Data Structures and Algorithms | 6 | Demetris Trihinas |
| MATH-225 | Probability and Statistics I | 6 | George Portides |
| MATH-280 | Linear Algebra I | 6 | George Chailos |
| BADM-332 | Technical Writing and Research | 6 | Katarzyna Alexander |
Semester 5
| Course ID | Course Title | ECTS Credits | Lecturer |
|---|---|---|---|
| COMP-321 | Theory of Computation | 6 | Ioanna Dionysiou |
| COMP-335 | Computer Organization and Architecture | 6 | Charalambos Christou |
| COMP-230 | Cybersecurity Governance | 6 | |
| COMP-242 | Data Privacy and Ethics | 6 | |
| COMP-263 | Human Computer Interaction | 6 |
Semester 6
| Course ID | Course Title | ECTS Credits | Lecturer |
|---|---|---|---|
| COMP-302 | Database Management Systems | 6 | Vasso Stylianou |
| COMP-354 | Operating Systems | 6 | Harald Gjermundrød |
| COMP-358 | Networks and Data Communications | 6 | Constandinos Mavromoustakis |
| COMP-289 | Web and Mobile Development | 6 | |
| COMP-340 | Big Data | 6 |
Semester 7
| Course ID | Course Title | ECTS Credits | Lecturer |
|---|---|---|---|
| COMP-405 | Artificial Intelligence | 6 | Athena Stassopoulou |
| COMP-417 | Parallel and Distributed Systems | 6 | Harald Gjermundrød |
| COMP-498 | Final Year Project I | 6 | Vasso Stylianou |
| COMP-345 | Robot Programming | 6 | |
| COMP-447 | Neural Networks and Deep Learning | 6 |
Semester 8
| Course ID | Course Title | ECTS Credits | Lecturer |
|---|---|---|---|
| COMP-401 | Software Engineering | 6 | Christos Mettouris |
| COMP-431 | Computer Security | 6 | Ioanna Dionysiou |
| COMP-499 | Final Year Project II | 6 | Vasso Stylianou |
| COMP-474 | Cloud Computing | 6 | |
| COMP-476 | Generative AI | 6 |
Note: The semester breakdown is indicative and includes ten Major Electives (COMP) courses out of the maximum of ten (minimum of 6) that a student can take from Section B. In general, the student has a choice on the number of electives to take from each section (B, C, D, E, and F) as long as the number of credits completed in each section, satisfies each section’s minimum credits and does not exceed its maximum number of credits.
Σημείωση: Το πιο πάνω πρόγραμμα ανά εξάμηνο είναι ενδεικτικό. Μερικά από τα μαθήματα είναι επιλογής και μπορούν να αντικατασταθούν με άλλα.




















