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

Apply Today

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.

Dr Andreas Savva

Associate Professor
School of Sciences and Engineering
Department of Computer Science

Dr Charalambos Christou

Associate Professor
School of Sciences and Engineering
Department of Computer Science
Member of the Senate

Dr Chris Christou

Associate Head of Department
Associate Professor
Department of Design & Multimedia
School of Humanities and Social Sciences

Dr Demetris Trihinas

Assistant Professor
School of Sciences and Engineering
Department of Computer Science

Dr Dmitry Apraksin

Director of IT (University Level)
IT Department
Assistant Professor
School of Sciences and Engineering
Department of Computer Science

Dr George Chailos

Associate Professor
School of Sciences and Engineering
Department of Computer Science

Dr George Portides

Assistant Professor
School of Sciences and Engineering
Department of Computer Science

Dr Stelios Neophytou

Head of Department
Associate Professor
School of Sciences and Engineering
Department of Engineering

Dr Vasso Stylianou

Associate Professor
School of Sciences and Engineering
Department of Computer Science

Professor Athena Stassopoulou

Head of Department
Professor
School of Sciences and Engineering
Department of Computer Science

Professor Constandinos Mavromoustakis

Professor
School of Sciences and Engineering
Department of Computer Science

Professor Harald Gjermundrod

Professor
School of Sciences and Engineering
Department of Computer Science

Professor Ioanna Dionysiou

Associate Head of Department
Professor
School of Sciences and Engineering
Department of Computer Science
Member of the Senate

Professor Ioannis Katakis

Professor
School of Sciences and Engineering
Department of Computer Science

Professor Marinos Themistocleous

Professor
Associate Dean
School of Business
Department of Digital Innovation
Director
Institute For the Future

Professor Nectarios Papanicolaou

Professor
School of Sciences and Engineering
Department of Computer Science
Member of the Council

Professor Philippos Pouyioutas

Rector
Professor
School of Sciences and Engineering
Department of Computer Science
Member of the Council, Member of the Senate

Dr Ali Tayari

Data Scientist/Machine Learning Analyst
IT Department
Institute For the Future

Dr Christos Mettouris

Adjunct Faculty

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Dr Demetris Paschalides

Adjunct Faculty

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Dr Michalis Agathocleous

Adjunct Faculty

Dr Moysis Symeonidis

Adjunct Faculty

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Mr Kyriakos Costa

Adjunct Faculty

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