Core courses (30 ECTS)

• Foundations of Artificial Intelligence (7.5 ECTS)
• Introduction to Machine Learning (7.5 ECTS)
• Knowledge Representation, Reasoning and the Semantic Web (7.5 ECTS)
• Big Data Analytics (7.5 ECTS)

Elective courses (30 ECTS)

• Advanced Topics in Machine Learning (7.5 ECTS)
• Artificial Neural Networks and Deep Learning (7.5 ECTS)
• Advanced Topics in Knowledge Representation and Reasoning (7.5 ECTS)
• Multi-Agent Systems and Game Theory (7.5 ECTS)
• AI in Video Games (7.5 ECTS)
• Robotics and Perception (7.5 ECTS)
• Natural Language Processing (7.5 ECTS)
• Philosophy and Ethics of AI (7.5 ECTS)
• One (1) Elective Course from a relevant distance learning M.Sc. program of the School of Sciences as this will be approved by the Program Coordinator

Master Thesis (30 ECTS)

The MSc in Artificial Intelligence at EUC aims to train and educate skilled leaders in the field and to address the emerging needs of the market. With an in-depth study of AI theory and practice, students are equipped with technical skills and an understanding of machine learning, big data analytics, AI in gaming and robotics, natural language processing and deep learning. Students undertake research with the Department’s laboratories and research centers and are equipped for employment in a range of industries or for doctoral studies in the field.

Compulsory Courses (60 ECTS)

• Fundamentals of Finance (10 ECTS)
• Advanced International Financial Reporting (10 ECTS)
• Quantitative Methods in Accounting and Finance (10 ECTS)
• Analytics in Accounting and Finance (10 ECTS)
• Computational Finance (10 ECTS)
• Applied Financial Analysis and Valuation (10 ECTS)

Elective Courses (10 ECTS)

• Financial and Managerial Accounting (10 ECTS)
• Principles of Programming for Python (10 ECTS)
• Principles of Programming for R (10 ECTS)
• Principles of Machine Learning (10 ECTS)
• Principles of Artificial Intelligence (10 ECTS)
• Ethics and Corporate Social Responsibility (10 ECTS)
• Investment and Risk Management (10 ECTS)
• One Elective course from another relevant Master Program of the University. Only one (1) course of this provision may be selected by the student (of at least same number of ECTS) throughout the completion of the program requirements, with the program coordinator’s approval.

The MSc Data Analytics in Accounting and Finance at EUC aims to train students in key concepts and theories in Accounting, Finance and Data Analytics.  The program equips students with advanced skills, scientific methodologies and analytical tools to meet the challenges of a fast-changing environment where vast amounts of data are available.  As new digital technologies continue to be widely adopted in the Accounting and Finance industry, there is an urgent need to equip students with the technological skills and knowledge necessary to use big data in decision-making in the current and future business environment. Data analytics applications impact virtually every business sector and industry, thus graduating students are equipped for a wide range of employment opportunities or for doctoral studies in the field.

The MA in CALL course is a 3-semester course of 90 ECTS credit. The course covers areas such as Teaching Methodologies, Instructional Technology, Technology Enhanced L2 Curriculum Development & Evaluation, Research Methods in Applied Linguistics, Computer Assisted Language Assessment and Testing, Emerging Technologies in Language Learning, CALL from the student perspective and research in the area of CALL.

It consists of eight modules of 7.5-ECTS credit each, and a 30 ECTs credit module on research in CALL. 

Modules Descriptions

• Acquisition (7,5 ECTS)
• Teaching Methodologies  (7,5 ECTS)
• Instructional Technology (7,5 ECTS)
• Computer Assisted Language Assessment and Testing (7,5 ECTS)
• Research Methods in Applied Linguistics (7,5 ECTS)
• Technology Enhanced Curriculum Development & Evaluation (7,5 ECTS)
• Emerging Technologies in Language Learning (7,5 ECTS)
• Call from the Student Perspective (7,5 ECTS)
• Dissertation (30 ECTS)

The programme aims to meet the needs of the local community and language teachers worldwide. 

It aims to develop the knowledge and skills needed today for professional careers in teaching second / foreign language with the use of new technologies  at all levels of education (pre-primary, primary, secondary, tertiary). It  focuses on learning theories, pedagogical methods and technological applications in language teaching. It is consistent with contemporary learning theories and methods in language teaching and deals with the theories and methods of applying new technologies in teaching and learning languages taught as a second (L2) or as a Foreign Language (FL). Although not limited to the teaching of English as a second / foreign language, the objectives of the proposed Master’s programme are consistent with the technological standards for the teaching of English as a Second Language (Teaching English as a Second Language Technology Standards Framework, 2008).

Upon completion of the programme, it is expected that students will have acquired specialised knowledge, skills and experiences in Computer Assisted Language Learning and in Autonomous and Lifelong Learning.

Intended Learning Outcomes (ILOs)

By the end of the programme, students will be able to:

1. Identify, discuss and apply learning theories, pedagogical methods and technological applications in second (L2) or Foreign Language (FL) teaching.
2. Acquire and employ specialised knowledge, skills and experiences in CALL and in Autonomous and Lifelong Learning.
3. Produce, critically evaluate, and revise curricula, materials, tasks, lesson plans, tests and technology-mediated activities aligned with contemporary learning theories and methods in language teaching.
4. Articulate, present results and report on research in a scientific manner.

TYPE AND NUMBER OF STUDENTS

The MA in CALL programme aims to attract language teachers from around the world (from government and private schools as well as tertiary education in Cyprus and Europe, Middle East, Africa, Asia, North America and Australia), seeking to attend a graduate programme in this subject and in this particular mode. The maximum number of students admitted is 15-20, following a competitive process, in order to maintain the high level of quality.

Modules

Compulsory

• Critical Analysis
• Projects & Programmes
• Masters Project

Optional

• Digital Security
• Network Operations & Management
• Web Application Development
• Mobile Application Development
• e-Marketing
• Wireless Networks & Communications
• Advanced Topics in User Experience
• Ethical Hacking
• ERP Systems
• Enterprise Data Management
• Mobile Application Development 
• Distributed Systems
• Network Communication & Routing
• Advanced Topics in IT Security
• Agile Systems Development 
• Exploratory Data analysis
• Information Security Management
• Independent Investigation
• Artificial Intelligence 
• Professional Placement

Computing-related technology, such as new mobile devices and applications are changing the way we communicate, do business and access news and entertainment. The MSc in Computing offers opportunities, to achieve professional certifications through specific modules: The Cisco CCNA1 exam can be taken after attending the Network Communications & Routing module and the Associate Android Developer exam after attending the Mobile Application Development module.

SPECIALISATIONS:

1. IT Security & Networking 
2. Mobile & Web Development
3. IT Management in Business

The MSc in Computing provides students with an opportunity to develop generic computing skills that can be applied in all walks of life as well as the skills and understanding needed to develop
software systems. Students will develop transferable skills in the evaluation of ideas and concepts, effective communication, synthesis of ideas and become reflective practitioners. The aims of the course are to provide an opportunity for the students to plan, undertake and evaluate a substantial computing Project; to develop the students’ critical evaluation, communication and self management skills to a level appropriate for post-graduate students; and to encourage and enable the students to become reflective and research-aware practitioners.

Modules

Compulsory

• Critical Analysis
• Digital Forensic Investigation
• Ethical Hacking
• Information Security Management
• Masters Project
• Cyber Defence

Optional

• Cyber Warfare
• Cyber Incident Handling 
• Practical Cryptography

The constant advancement of technology and the introduction of cloud services, smart devices and wireless communications as well as the increasing penetration of the Internet in our everyday activities and the sharing of sensitive information through it, have created a need for information assurance and data security.

This programme will appeal to people with an interest in understanding cybersecurity issues with emphasis in areas such as cyber warfare, cyber defence, ethical hacking, network forensics and information security management. The programme will provide students with the specialised knowledge required, including theory, technologies and relevant design techniques, as a prerequisite for designing secure networks.

During the programme students will have the opportunity to apply their theoretical knowledge through specialised physical, virtual and remote security laboratories in which they will be able to carry out activities such as reconnaissance, network scanning and exploitation exercises, and investigate the usage and behaviour of security systems such as Intrusion Detection Systems. As part of the programme, students will also develop generic and domain-specific research techniques and skills required for successfully completing their final year MSc Thesis project.

Modules

Compulsory

• Critical Analysis
• Digital Forensic Investigation
• Ethical Hacking
• Information Security Management
• Masters Project
• Cyber Defence

Optional

• Cyber Warfare
• Cyber Incident Handling 
• Practical Cryptography

The constant advancement of technology and the introduction of cloud services, smart devices and wireless communications as well as the increasing penetration of the Internet in our everyday activities and the sharing of sensitive information through it, have created a need for information assurance and data security.

This programme will appeal to people with an interest in understanding cybersecurity issues with emphasis in areas such as cyber warfare, cyber defence, ethical hacking, network forensics and information security management. The programme will provide students with the specialised knowledge required, including theory, technologies and relevant design techniques, as a prerequisite for designing secure networks.

During the programme students will have the opportunity to apply their theoretical knowledge through specialised physical, virtual and remote security laboratories in which they will be able to carry out activities such as reconnaissance, network scanning and exploitation exercises, and investigate the usage and behaviour of security systems such as Intrusion Detection Systems. As part of the programme, students will also develop generic and domain-specific research techniques and skills required for successfully completing their final year MSc Thesis project.

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COMPULSORY

• Masters Project
• Critical Analysis
• Exploratory Data Analysis
• Enterprise Data Management
• Knowledge Discovery
• Business Intelligence and Data Analytics

OPTIONAL

• Information Security Management
• Advanced Topics in Human Computer Interaction (HCI)
• UX Away from the Desktop
• Strategy and International Management
• ERP Systems
• e-Marketing
• Leadership and Management

Data Analytics is the science that allows decision makers to unveil new business insights by examining large amounts of data to uncover hidden patterns, correlations and other important insights. This course is designed to provide graduates and working professionals with knowledge and a diverse set of skills that span across all layers of the knowledge discovery stack including storage, mining, analytics, decision support frameworks and visualisations, as well as practical experience with modern tools.

In particular, students will learn how to (i) analyse large data sets and summarise their main characteristics with the use of attractive data visualisations; (ii) design and create databases that allow organisations to efficiently manage and query their enterprise data; (iii) discover patterns in large data sets with established techniques from various fields such as statistics, machine learning and artificial intelligence; and (iv) understand today’s turbulent business environment and learn how modern BI tools enable organisations to survive and excel.

The MSc Data Analytics programme at UCLan Cyprus is the only programme in Cyprus which offers the SAS Joint Certificate. UCLan Cyprus MSc Data Analytics graduates have the option to receive the SAS Joint Certificate in Business Intelligence and Data Mining in addition to their MSc award. The SAS Joint Certificate equips students with additional knowledge and skills to apply analytics to real business problems using real business data and provides students with a competitive advantage in the marketplace, through a professional certification which is in high demand by the market. The combination of the MSc Data Analytics programme and the SAS Joint certificate curriculum prepares graduates to work in a data-rich business environment and have a rewarding career in the digital age.

Program Requirements
The European Credit Transfer and Accumulation System (ECTS in short) is a tool of the European Higher Education Area for making studies and courses more transparent. It helps students to move between countries and to have their academic qualifications and study periods abroad recognized. The credits below are based on the ECTS.

To graduate, students are required to earn 90 credits as follows:

78 credits from taught core courses (including final project),
12 credits either from one of the three concentration tracks, or by combining courses from different tracks.

CORE COURSES
Basic Functional Skills

• Foundations of Business Information Technology Credits: 6
• Database Management and Cloud Computing Credits: 6
• Data Mining, Visualization and Decision Making Credits: 6
• Managing Big Data Credits: 6
• Python Programming Credits: 6
• Information Security Management for Business Credits: 6
• Web & Social Media Analytics Credits: 6
• Digital Transformation of Business & Organizations Credits: 6
• Quantitative Methods & Statistical Analysis Credits: 6
• Data Analytics and Artificial Intelligence Credits: 6
• Ethics, CSR & Sustainability Credits: 6
• Data Science Research Project Credits: 6

ELECTIVE COURSES
Operations & Project Management (12/24 ECTS)

• Operations & Supply Chain Management Credits: 6
• Project Management Credits: 6
• Project Management in Information Technology Credits: 6
• Blockchain and Applications Credits: 6

ELECTIVE COURSES
Technical Entrepreneurship & Innovation (12/24 ECTS)

• Technical Entrepreneurship Credits: 6
• Digital Business Tools and Digital Business Development Credits: 6
• Project & Business Financing Credits: 6
• Planning & Starting a New Business Credits: 6

ELECTIVE COURSES
Financial Services (12/30 ECTS)

• Innovative Financial Technologies (FinTech) Credits: 6
• Financial Innovation and Financial Regulation Credits: 6
• Project & Business Financing Credits: 6
• Digital Business Tools and Digital Business Development Credits: 6
• Blockchain and Applications Credits: 6

Program Overview
The Master of Science (MSc) in Business Intelligence and Data Analytics is designed to equip the students with the necessary knowledge and a diverse set of skills required throughout the data analytics lifecycle. This skillset includes business data requirements, data acquisition and integration, data storage, data processing, data analysis, insights derivation, and ultimately, the business deployment of derived insights in a meaningful and successful manner.

It is a unique and innovative-by-design postgraduate degree that combines both managerial and technical aspects around the data science field. Particular emphasis is given to students acquiring practical skills for implementing data science solutions, as well as enhancing their decision-making capabilities in Information Technology from a data science perspective.

The curriculum is designed to transform the participants into data scientists and equip them with the knowledge and skillset required to contribute and compete in the rapidly advancing data-driven economy.

The program is nationally accredited by CYQAA and recognized by KYSATS.

Semester 1

• Digital Fabrication (10 ECTS)
• Theory and Evolution of Computational Design (10 ECTS)
• Computational Design Processes (10 ECTS)

Semester 2

• Robotic Fabrication (10 ECTS)
• Interactive Design (10 ECTS)
• Performance Based Design (10 ECTS)

Semester 3

• Research Methodology in Design and Technology (10 ECTS)
• Thesis (20 ECTS)

The above semester breakdown is an indicative one. A few of the courses are electives and can be substituted by others. 

The MSc in Computational Design and Digital Fabrication is offered in collaboration with the University of Innsbruck, Institute for Experimental Architecture Hochbau. The programme explores the relationship between computational tools and architectural design, in an effort to attain a new insight into the relationship between design intent and built form. Prospective participants will have the opportunity to develop computational design skills and acquire hands on cutting-edge fabrication experiences, while cultivating analytical and creative thinking on the applications of computation in design. Furthermore, the programme aims at promoting international exchange of research knowledge, through the connection to the University of Innsbruck and its Robotic Lab (REXLAB) at the Institute for Experimental Architecture. This encourages participants to become part of the global community of computational research in digital fabrication, a growing industry increasingly important for the production of the built environment.

Degree Requirements    

• Compulsory Courses 70 ECTS
• Master Thesis 20 ECTS
• Total Requirements 90 ECTS

Core Courses

• Introduction to Programming and Object Orientation (10 ECTS)
• Data Structures & Algorithms (10 ECTS)
• Computer Architecture and Hardware (10 ECTS)
• Operating Systems (10 ECTS)
• Databases and Information Management Systems (10 ECTS)
• Computer Networks & the Internet (10 ECTS)
• Software Engineering (10 ECTS)

Master Thesis    

Option A. Select two out of the following elective courses:

• Web Technologies and Development (10 ECTS)
• Algorithms and Complexity (10 ECTS)
• Data Mining and Machine Learning (10 ECTS)
• Human-Computer Interaction (10 ECTS)

Or Option B:

• Research Project (20 ECTS)    

The MSc in Computer Science at EUC enables students from other disciplines (e.g., Mathematics, Physics, Education), along with Computer Science graduates, to develop advanced skills and knowledge in core and specialized topics in the field. Following a comprehensive and global view of computer science’s core areas, students choose a specialization in an emerging technological area such as Machine Learning, Web Technologies and Human-Computer Interaction.

A major component of the program is the research project in which students undertake independent, scientific research and development work, preparing them to undertake PhD level studies or enter a wide range of careers across countless industries.

Program Requirements
The European Credit Transfer and Accumulation System (ECTS in short) is a tool of the European Higher Education Area for making studies and courses more transparent. It helps students to move between countries and to have their academic qualifications and study periods abroad recognized. The credits below are based on the ECTS.

To graduate, students are required to earn 90 credits as follows:

• 78 credits from taught core courses (including Research Project),
• 12 credits from taught elective courses.

CORE COURSES
Basic Functional Skills

• Foundations of Business Information Technology Credits: 6
• Quantitative Methods & Statistical Analysis Credits: 6
• Python Programming Credits: 6
• Database Management and Cloud Computing Credits: 6
• Web Application Development Credits: 6
• Object Oriented Programming Credits: 6
• Blockchain and Applications Credits: 6
• Applied Artificial Intelligence & Deep Learning Credits: 6
• Digital Transformation  of Businesses & Organizations Credits: 6
• Algorithms and Data Structures Credits: 6
• Mandatory Research Project Credits: 18

ELECTIVE COURSES

• Information Security Management for Business Credits: 6
• Project Management in Information Technology Credits: 6
• Technical Entrepreneurship Credits: 6
• Data Mining, Visualization, and Decision Making Credits: 6
• Applied Data Analytics, Visualization, and Forecasting Credits: 6

Program Overview
The Master of Science (MSc) in Computer Science and Business Technologies program covers computer science technologies that can be applied to businesses to improve productivity, address modern needs, and create new potentials. Technology and digitization are increasingly entering our daily lives, society, business, economy and government. This is necessary to improve efficiency, remain functional, competitive and even safe. There is a general consensus that the use of technology in our daily lives and in our working practices whether in business or the professions will continue to increase and even accelerate.

The program combines computer science and business technologies with the development of skills in business technical management. The different aspects of the program are developed in parallel. The computer science part starts with introductory topics that provide the necessary theoretical background to comprehend modern programming languages and technologies. Some of these technologies involve databases and the cloud. Another general topic is artificial intelligence for decision making as well as the application of machine learning and deep neural networks to the analysis of big-data.

The program is nationally accredited by CYQAA and recognized by KYSATS.

Semester 1

• Cyber-Physical Systems and the Internet of Things
• Cryptography and Network Security
• Distributed Systems

Semester 2

• Research Seminars and Methodology
• Cyber Warfare
• Ethical Hacking
• Project in Cyber Security

Semester 3

• Thesis

The Master degree in Computer Science advances the students’ knowledge in core areas of computer science beyond the undergraduate level and exposes them to current and emerging trends.

The program provides an introduction to research within the field while strengthening the candidate’s effective application of computer science methods. The proposed Master degree in Computer Science is designed to have the learning outcomes related to: knowledge and understanding, application of knowledge and understanding for the analysis, design and development of computer systems. The curriculum prepares the student for a wide variety of computer-oriented careers, such as research, development, management, and teaching. The degree constitutes an independent and terminal study in addition to providing the basis for acceptance to, and continued studies towards, a doctoral degree in computer science.

The program aims of the specialization in Cyber Security focus on the impact of cyber warfare in the contemporary digital era and the analysis of threats, vulnerabilities and risks in a network environment. It also focuses on penetration testing principles and approaches to mitigate potential network attacks.

The program aims of the specialization in Mobile Systems focus on the fundamental concepts of Mobile Computing and wireless technology as well as on the development of software and applications for mobile platforms.

The program aims of the specialization in Blockchain Technologies focus on the fundamentals of digital currencies and the underlying blockchain technology. It also focuses on programmable smart contracts and the associated architectures such as Ethereum. It aims to prepare students on the possible impact of these technologies on various applications including those based on Artificial Intelligence, Machine Learning and Internet of Things.

Occupational Profiles of Graduates with Examples

Graduates of the MSc programme should be able to:

• hold managerial positions in the ICT industry or government offices;
• become senior technical developers or administrators in the ICT marketplace;
• become entrepreneurs and establish their own enterprises;
• continue studying towards a doctoral degree.

In addition, graduates of the Cyber Security concentration will be well-suited for positions within government and private industry and should be able to:

• work as Chief Information Security Officers
• become System, Network, and/or Web Penetration Testers
• become Computer Network Defense Analysts
• hold positions such as Security Consultants as well as System and Application Developers

The specialization in Mobile Systems, will enable graduates to:

• become senior technical developers and Mobile Systems Experts providing Mobile computing solutions
• hold managerial positions in the Mobile Systems industry
• hold critical positions in Mobile industry operators

Alternatively, the specialization in Blockchain Technologies, will enable graduates to:

• work as senior Blockchain engineers developing new decentralized solutions
• work as Blockchain Architects designing new blockchain systems
• hold positions like Blockchain Advisors or Consultants

Access to Further Studies

Graduates of the programme can be accepted into Third Cycle degrees (Doctorate Degree)

Semester 1

• Cyber-Physical Systems and the Internet of Things (10 ECTS)
• Cryptography and Network Security (10 ECTS)
• Distributed Systems (10 ECTS)

Semester 2

• Research Seminars and Methodology (6 ECTS)
• Cyber Warfare (10 ECTS)
• Ethical Hacking (10 ECTS)
• Project in Cyber Security (4 ECTS)

Semester 3

• Network Defence and Countermeasures (10 ECTS)
• Mobile Computing (10 ECTS)
• Machine Learning and Data Mining (10 ECTS)

The above semester breakdown is an indicative one. A few of the courses are electives and can be substituted by others.

The Master degree in Computer Science advances the students’ knowledge in core areas of computer science beyond the undergraduate level and exposes them to current and emerging trends.

The program provides an introduction to research within the field while strengthening the candidate’s effective application of computer science methods. The proposed Master degree in Computer Science is designed to have the learning outcomes related to: knowledge and understanding, application of knowledge and understanding for the analysis, design and development of computer systems. The curriculum prepares the student for a wide variety of computer-oriented careers, such as research, development, management, and teaching. The degree constitutes an independent and terminal study in addition to providing the basis for acceptance to, and continued studies towards, a doctoral degree in computer science.

The program aims of the specialization in Cyber Security focus on the impact of cyber warfare in the contemporary digital era and the analysis of threats, vulnerabilities and risks in a network environment. It also focuses on penetration testing principles and approaches to mitigate potential network attacks.

The program aims of the specialization in Mobile Systems focus on the fundamental concepts of Mobile Computing and wireless technology as well as on the development of software and applications for mobile platforms.

The program aims of the specialization in Blockchain Technologies focus on the fundamentals of digital currencies and the underlying blockchain technology. It also focuses on programmable smart contracts and the associated architectures such as Ethereum. It aims to prepare students on the possible impact of these technologies on various applications including those based on Artificial Intelligence, Machine Learning and Internet of Things.

Career Prospects

Graduates of the MSc programme should be able to:

• hold managerial positions in the ICT industry or government offices;
• become senior technical developers or administrators in the ICT marketplace;
• become entrepreneurs and establish their own enterprises;
• continue studying towards a doctoral degree.

In addition, graduates of the Cyber Security concentration will be well-suited for positions within government and private industry and should be able to:

• work as Chief Information Security Officers
• become System, Network, and/or Web Penetration Testers
• become Computer Network Defense Analysts
• hold positions such as Security Consultants as well as System and Application Developers

The specialization in Mobile Systems, will enable graduates to:

• become senior technical developers and Mobile Systems Experts providing Mobile computing solutions
• hold managerial positions in the Mobile Systems industry
• hold critical positions in Mobile industry operators

Alternatively, the specialization in Blockchain Technologies, will enable graduates to:

• work as senior Blockchain engineers developing new decentralized solutions
• work as Blockchain Architects designing new blockchain systems
• hold positions like Blockchain Advisors or Consultants

Access to Further Studies

Graduates of the programme can be accepted into Third Cycle degrees (Doctorate Degree)

Degree Requirements

• Compulsory courses 52 ECTS
• Elective Courses 16 ECTS
• Master Thesis 22 ECTS
• Total Requirements 90 ECTS

Compulsory courses

• Introduction to Cybersecurity (7 ECTS)
• Communications and Network Security (7 ECTS)
• Cryptography (8 ECTS)
• Cybersecurity Policy, Governance, Law and Compliance (10 ECTS)
• Cybersecurity Risk Analysis and Management (10 ECTS)
• Cybersecurity Architecture and Operations (10 ECTS)        

Elective courses
Students select two from the following courses

• Current Trends in Cybersecurity (8 ECTS)
• Machine Learning for Cybersecurity (8 ECTS)
• Data Privacy in the era of Data Mining and AI (8 ECTS)
• Ethical Hacking and Penetration Testing (8 ECTS)
• Incident Response and Forensic Analysis (8 ECTS)

Master Thesis

• Master Thesis (22 ECTS)

The MSc in Cybersecurity at EUC addresses the increasing demand for innovative approaches to the complexities and multidisciplinary character of cyber security policy and practice.  Students are equipped with technical skills and an understanding of law, risk management, ethical hacking and cryptography as these relate to cybersecurity. Students gain skills allowing them to develop and implement cyber security policies in public and private organizations. 

Students undertake research with the Department’s laboratories and research centers and are equipped for employment in a range of industries or for doctoral studies in the field.

Graduates work in:

• Digital Security Consultancy
• E-Commerce Digital Security
• Corporate Security
• Law Enforcement Authorities
• Internet Service Providers

Degree Requirements

• Compulsory courses 60 ECTS
• Master Thesis 30 ECTS
• Total Requirements 90 ECTS

Compulsory courses

• Introduction to Cybersecurity (10 ECTS)
• Communications and Network Security (10 ECTS)
• Cryptography (10 ECTS)
• Cybersecurity Policy, Governance, Law and Compliance (10 ECTS)
• Cybersecurity Architecture and Operations (10 ECTS)
• Ethical Hacking and Penetration Testing (10 ECTS)

Master Thesis

• Master Thesis (30 ECTS)

or        

Elective courses (only if Master Thesis is not selected)    

• Research Methods and two of the following (10 ECTS)
  • Special Cybersecurity Topics (10 ECTS)
  • Cybersecurity Risk Analysis and Management (10 ECTS)
  • Data Privacy in the Era of Data Mining and A (10 ECTS)
  • Incident Response and Forensic Analysis (10 ECTS)

The MSc in Cybersecurity at EUC addresses the increasing demand for innovative approaches to the complexities and multidisciplinary character of cyber security policy and practice.  Students are equipped with technical skills and an understanding of law, risk management, ethical hacking and cryptography as these relate to cybersecurity.

Students gain skills allowing them to develop and implement cyber security policies in public and private organizations.  Students undertake research with the Department’s laboratories and research centers and are equipped for employment in a range of industries or for doctoral studies in the field.

Semester 1

• Data Programming  (10 ECTS)
• Mathematics for Data Science   (10 ECTS)
• Data Privacy and Ethics  (10 ECTS)

Semester 2

• Machine Learning  (10 ECTS)
• Managing and Visualizing Data  (10 ECTS)
• Research Seminars and Methodology (4 ECTS)
• Project in Data Science   (6 ECTS)

Semester 3 (Non-Thesis Option)

• Deep and Reinforcement Learning  (10 ECTS)
• Big Data Management and Processing  (10 ECTS)
• Artificial Intelligence  (10 ECTS)

Semester 3

• Thesis  (30 ECTS)

The above semester breakdown is an indicative one. A few of the courses are electives and can be substituted by others. 

The aim of this program is to provide the students with advanced technical skills and a scientific understanding of Data Science. Moreover, the MSc will aid students in developing research competency so they can design their own scientific methods pushing the frontiers of this new emerging field. Finally, special emphasis is given to the development of skills that are required by the relevant cutting-edge industries.

Data Science is an applied science providing innovations and disrupting multiple industries ranging from Information and Communication Technologies and Medicine, to Journalism and Finance. The University of Nicosia has developed partnerships with instructors from the industry and this will enable the development of skills that are currently required by the industry. The MSc will develop full-stack research data scientists that are able to collect requirements, innovate, design, implement and critically evaluate a data science solution.

More specifically, the program aims at:

1. Providing students with the technical and analytical skills required for acquiring, managing, analyzing and extracting knowledge from heterogeneous data sources. Critical skills will be developed that aid students in making decisions on the appropriate data analysis pipeline. Students will be able to collect requirements, design, implement and evaluate a data science solution.
2. Providing students with software engineering and machine learning skills to design and implement scalable, reliable and maintainable solutions for data-oriented problems.
3. Enabling students to develop data programming skills for multiple business domains and possible challenges (Big Data, Streaming Data, Noisy Data, etc.).
4. Enabling students to assess and provide solutions for the privacy and ethical issues that arise at the application of data science methods to many real-world problems.
5. In collaboration with instructors from the industry, the student will be aware of the challenges that a professional comes across when moving from theory to practice and know how to overcome these challenges.
6. Giving the opportunity to the student to work in real world problems with real data in collaboration with industrial partners. Students will gain hands-on experience with the state-of-the-art data science technologies like Deep and Reinforcement learning.
7. Preparing students to pursue a PhD in data science or to any other field where data science skills are required (e.g. bioinformatics, computational social science, data driven journalism, etc.)
8. Providing students with a strong sense of social commitment, global vision and independent self-learning ability.

First Semester    

• DSC 510: Introduction to Data Science and Analytics (offered by CS) 8 ECTS
• DSC 530: Probability and Statistics for Data Science (offered by MAS) 8 ECTS
• DSC 531: Statistical Simulation and Data Analysis (offered by MAS) 8 ECTS
• One Free Elective Course (offered by other entities of the University of Cyprus, e.g. Department of Law, Center for Entrepreneurship etc.) 4 ECTS

Second Semester    

• DSC 511: Big Data Analytics (offered by CS) 8 ECTS
• DSC 550: Business Analytics Applications (offered by BUS) 8 ECTS
• DSC 532: Statistical Learning (offered by MAS) 8 ECTS
• One Free Elective Course (offered by other entities of the University of Cyprus, e.g. Department of Law, Center for Entrepreneurship etc.) 4 ECTS

Summer Semester    

• Capstone Project in Data Science (1st Phase) 5 ECTS

Third Semester    

• Computer Science Track/ Statistics Track/Business Analytics Track Course 8 ECTS
• Computer Science Track/ Statistics Track/Business Analytics Track Course 8 ECTS
• Computer Science Track/ Statistics Track/Business Analytics Track Course 8 ECTS
• Capstone Project in Data Science (2nd Phase) 5 ECTS

The MSc in Data Science programme brings together the expertise of three departments in the University of Cyprus – Business and Public Administration, Computer Science, and Mathematics and Statistics – to prepare the next generation of data-oriented thinkers.

Data science is a modern interdisciplinary field that uses scientific methods, processes, algorithms and systems in order to extract knowledge and insights from data. The programme’s objective is to offer a strong understanding of basic and advanced methods in statistical inference, machine learning, data visualization, data mining, and business analytics.

The programme is designed for students that have a background in STEM or in Business and Economics, who can demonstrate good knowledge of English, and who, as part of their undergraduate degree, have completed an introductory statistics course, as well as a course in a programming language such as Python and/or R (see Admissions for further information).

The duration of the programme is 18 months (90 ECTS). The first two semesters are dedicated to core courses, and homogenize students’ knowledge on the basics of data science. The third semester allows students to select one of three tracks: Computational Science, Statistics, and Business Analytics. In the summer semester the Capstone project, brings students in contact with real world problems and helps them cement the knowledge and skills they acquired.

At the completion of the programme, students will have gained skills that are critical in a modern data-driven world, and will be in a position to think across disciplines and to transform data into actionable insights.

Communication Systems

SEMESTER 1

• ADVANCED DIGITAL COMMUNICATION SYSTEMS I
• RANDOM VARIABLES AND STOCHASTIC PROCESSES
• DIGITAL SIGNAL PROCESSING
• GRADUATE SEMINARS I
• TECHNICAL ELECTIVE

SEMESTER 2

• ADVANCED DIGITAL COMMUNICATION SYSTEMS II
• GRADUATE SEMINARS II
• RESEARCH PREPARATION AND PROPOSAL
• TECHNICAL ELECTIVE
• TECHNICAL ELECTIVE

SEMESTER 3

• GRADUATE RESEARCH
• THESIS WRITING AND PRESENTATION
• TECHNICAL ELECTIVE

Power Systems

SEMESTER 1

• POWER TRANSMISSION LINES
• RENEWABLE ENERGY SOURCES AND SUSTAINABILITY
• POWER SYSTEM ANALYSIS
• GRADUATE SEMINARS I
• TECHNICAL ELECTIVE

SEMESTER 2

• ELECTROMAGNETIC ENERGY CONVERSION
• GRADUATE SEMINARS II
• RESEARCH PREPARATION AND PROPOSAL
• TECHNICAL ELECTIVE
• TECHNICAL ELECTIVE

SEMESTER 3

• GRADUATE RESEARCH
• THESIS WRITING AND PRESENTATION
• TECHNICAL ELECTIVE

Control Systems

SEMESTER 1

• MODERN CONTROL SYSTEMS
• LINEAR SYSTEMS ANALYSIS
• DIGITAL CONTROL SYSTEMS
• GRADUATE SEMINARS I
• TECHNICAL ELECTIVE

SEMESTER 2

• RANDOM VARIABLES AND STOCHASTIC PROCESSES
• GRADUATE SEMINARS II
• RESEARCH PREPARATION AND PROPOSAL
• TECHNICAL ELECTIVE
• TECHNICAL ELECTIVE

SEMESTER 3

• GRADUATE RESEARCH
• THESIS WRITING AND PRESENTATION
• TECHNICAL ELECTIVE

Computer Engineering

SEMESTER 1

• DIGITAL SYSTEM DESIGN
• COMPUTER ORGANIZATION AND ARCHITECTURE
• DATA AND COMPUTER NETWORKS
• GRADUATE SEMINARS I
• TECHNICAL ELECTIVE

SEMESTER 2

• ADVANCED COMPUTER ARCHITECTURE
• GRADUATE SEMINARS II
• RESEARCH PREPARATION AND PROPOSAL
• TECHNICAL ELECTIVE
• TECHNICAL ELECTIVE

SEMESTER 3

• GRADUATE RESEARCH
• THESIS WRITING AND PRESENTATION
• TECHNICAL ELECTIVE

The Program aims to provide the graduates with scientific knowledge, research expertise and competences in order to meet the challenging market needs and prepare them for their professional development in engineering design as well for pursuing graduate studies at the Doctorate (PhD) level.

The main objectives of the Program are to:

1. Develop the students’ capacity to critically think and creatively address advanced Electrical Engineering Topics.
2. Develop the technical written and oral presentation skills of the students in order to effectively disseminate their work in the form of well-structured reports and presentations. 
3. Equip students with postgraduate level knowledge, tools and methodologies on Advanced Electrical Engineering Topics pertinent to three areas of study: generation transmission and distribution of Electric Power via conventional or renewable energy sources, Telecommunication Systems and Automation and Control Systems
4. Equip students with competent skills and experience, developing their ability to engage in the engineering design process via a systematic breakdown of real world problems, identification of design requirements and the utilization of analytical, software and experimental tools for the analysis, design, development and performance evaluation of effective solutions.
5. Develop student awareness on recent advancements, key technologies, future trends and state of the art challenges in Electrical Engineering.
6. Develop the ability of students to continuously learn and self-develop by accessing appropriate information sources as for example textbooks, research articles, online resources and seminars.  
7. Engage students in the research process by successfully applying the research methodology in a guided manner.
8. Engage students in research activities in key technology fields and help them to acquire the required knowledge and develop the necessary skills that will allow them to adapt and evolve in the fast evolving discipline of Electrical Engineering and pursue further Doctoral Studies.
9. Develop the students’ transferable skills needed to ensure a successful academic or professional career in the field of Electrical Engineering,
10. Prepare the students for direct employment after graduation by integrating theory with practice, through activities like work placement and the preparation for certification exams.

Key Learning Outcomes

1. Analyze real world problems in control communication and power systems, identifying their design requirements and develop and evaluate effective solutions by applying the design procedure involving the problem breakdown, modeling and design and performance evaluation.     
2. Identify the theoretical foundations of communications controls and power system analysis theory.
3. Use analytical methods and modelling techniques to evaluate electrical engineering systems (control, communication, power) and components in terms of general quality attributes and possible trade-offs presented within the considered problems.
4. Analyse and design communication systems and key enabling technologies for next generation networked systems. and demonstrate awareness on the capabilities and limitations of existing and emerging communication systems.
5. Evaluate the capabilities and limitations of existing and emerging technologies in the field of power generation, transmission and distribution using sustainable and renewable energy sources.
6. Plan, design and manage industrial electrical power systems, taking into account the integration of information and communication technologies rendering the aforementioned systems “Smart”.
7. Demonstrate awareness on the forefront of knowledge in modern control theory in the field of Automation and Control Systems and how these technologies can be combined with Information and Communication Technologies and Power Systems leading to Intelligent Networks and Cyber-physical Systems. 
8. Design, analyse, optimise and control complex industrial automated systems.
9. Develop competency in the research methodology.
10. Retrieve, analyze and evaluate information from different sources, including information retrieval through databases and on-line computer searches.
11. Demonstrate awareness on the role of engineers in society and the professional and ethical responsibilities of engineers.
12. Report research results and new designs in well-structured written reports and present the obtained results using presentations. 

The language of instruction of the program is English

Occupational Profiles of the Graduates

The graduates of the Program have the knowledge and skills required for the design, implementation, maintenance and administration of electrical systems related to their specialization.

Communication Systems graduates can be employed in public or private sector at internet and cellular communication providers, or communication infrastructure design and maintenance.

Power Systems graduates can seek employment in public or private sector industries related to electric power generation and distribution, companies activating in renewable energy systems, or as electrical engineer in industrial facilities.

Control Systems graduates can be employed in industry as production chain engineers, or in the design and development of automated, remotely controlled systems, and their control panels.

SEMESTER 1

• Digital Innovation and Entrepreneurship (7.5 ECTS)
• Disruptive Technologies (7.5 ECTS)
• IT Project Management (7.5 ECTS)
• Research Methods (7.5 ECTS)

SEMESTER 2

• Information Systems Analysis and Design (7.5 ECTS)
• Problem-Solving Programming (7.5 ECTS)
• Big Data and Analytics (7.5 ECTS)

Elective

• Digital Marketing (7.5 ECTS)
• Information Security (7.5 ECTS)
• Mobile Application Development (7.5 ECTS)

SEMESTER 3

• Dissertation (30 ECTS)

MSc in Information Systems and Digital Innovation is an innovative and multidisciplinary programme that integrates knowledge on the development and management of Information Systems to study emerging technologies of Digital Innovation, such as Big Data, the Internet of Things, Artificial Intelligence, and Robotics.

The Programme aims to provide each student with a comprehensive understanding of how to use Digital Technologies to improve businesses in today’s digital economy and explore the management and innovation aspects of Information Technologies.

SEMESTER 1

• Disruptive Technologies (7,5 ECTS)
• Digital Innovation and Entrepreneurship (7,5 ECTS)
• IT Project Management (7,5 ECTS)
• Research Methodology (7,5 ECTS)

SEMESTER 2

• Information Systems Analysis and Design (7,5 ECTS)
• Problem-Solving Programming (7,5 ECTS)
• Big Data and Analytics (7,5 ECTS)
• Information Security (7,5 ECTS)

SEMESTER 3

• Dissertation (30 ECTS)

The MSc in Information Systems and Digital Innovation is an innovative and multidisciplinary program with the objective to integrate the knowledge about the design and development of Information Systems with the disruptive technologies of Digital Innovation. Examples of such disruptive technologies are Big Data, the Internet of Things, Artificial Intelligence, Blockchain, and Robotics.

Nowadays, technology has a massive impact on business operations. The formula for business success is simple: drive innovation with information technology. Realizing the challenges that technology presents is the key to success your business goals, retain and raise the number of your customers in the process. Therefore, it is essential to integrate new technologies in businesses. In our days, lots of firms are prioritizing innovation as a key to their business strategy. Therefore, companies and their directors must understand technology, build their technical proficiency, implement technologies that matter to them and gain an advantage in managing their organization.

ADVANTAGES OF THE PROGRAMME

• The international prestige and recognition of the Neapolis University of Pafos.
• Excellent academic staff with strong expertise in the taught subjects.
• International collaborations with many Universities.
• The use of advanced technology and resources.
• High Academic Calibre of the teaching staff.
• Competitive tuition fees.

The MSc in Information Systems and Digital Innovation aims at postgraduate education and scientific specialization in Information Systems and Digital Innovation, targeting a more professional knowledge and a broader education of students with a specific interest in this subject. It is primarily aimed at graduates of Computer Science, Computer Engineering and Economic Studies.

• Taught by Leading Faculty and World-renowned Industry Experts
• Learn the technical and business aspects of the Metaverse
• Includes world’s first MOOC “NFTs and the Metaverse” delivered exclusively on-chain and in the metaverse.
• Join the largest metaverse student community in the world (22,500+ students)
• Over €300,000 in Scholarships Annually

Degree Objectives

The MSc in Metaverse is designed to provide participants a specialized program of study to become competent professionals in the field of Metaverse. Graduates will benefit from a broad spectrum of advanced courses.

Students are exposed to an enriching and stimulating curriculum that includes compulsory courses on the NFTS and the Metaverse, Web 3.0 architecture and digital assets, Extended Reality, monetizing digital creativity, virtual world architectures, social, legal and ethical issues in the Metaverse. In addition, students can select elective courses that focuses on advanced topics such as virtual economies, token economics, data science for the Metaverse, emerging topics in Metaverse, virtual and augmented reality development, game programming, smart contract programming, blockchain systems and architectures, interactive design.

Theoretical principles, state-of-the-art research, and Metaverse related case studies, tools and frameworks are mastered by students who may also select to advance their programming skills and become highly skilled developers or specialize in financial/management aspects and become highly literate consultants, entrepreneurs, or financial professionals. The degree constitutes an independent and terminal study in addition to providing the basis for acceptance to, and continued studies towards, a doctoral degree or to other areas of study.

Learning Outcomes

Upon successful completion of the program graduates are expected to:

1. Acquire knowledge and expertise in Metaverse systems.
2. Conduct research leading to new knowledge in Metaverse.
3. Propose original applications of analysis and research knowledge in the field of Metaverse.
4. Unfold leadership skills, through teamwork, relative in Metaverse with the purpose of enriching current practices or introducing new processes that can be used to design, implement, gain value and manage Metaverse applications.
5. Develop the capacity to creatively deal with complex problems either individually or as part of a group through research or practical projects.
6. Critically evaluate Metaverse systems and solutions, and apply theory, practices and tools for their specification, design, implementation, maintenance, and management.
7. Communicate clearly and analytically using techniques derived from scientific practice in group meetings, presentations, lectures, written reports, and research papers.
8. Exhibit such skills that are required to participate in research and development work or to independently work in other qualified areas as well as be able to continue studies towards a doctoral degree.

Teaching Methodology

The program is offered through distance learning so as to be accessible to all interested students, irrespective of their geographic location. Within the distance-learning paradigm, the program deploys various teaching methods: while the majority of the courses consist of lectures delivered by the faculty course lecturer(s), in some cases it may be deemed appropriate and beneficial to host guest lecturers with academic and business background related to topics covered in courses.

Moreover, practical exercises, individual and group projects, simulations, and case study analyses, will form an integral part of the teaching methodology employed in the program.

The program gives students the opportunity to acquire deeper knowledge and skills in the field of Metaverse Systems. This is a relatively new area of practice and research that is expected to provide ample employment opportunities for program graduates in various and inter-disciplinary positions.

The program is both theoretical and practical and has been designed to allow the students to choose those elective courses that will meet their future career goals. Regardless of the stream chosen by students, each instructor strives to create an inspiring atmosphere for the students and enhances the learning experience.

Graduates of the program may become:

• Metaverse Project Manager
• Metaverse Business Development Manager
• Metaverse token and NFT expert
• Metaverse Data Scientist/Analyst
• Metaverse Entrepreneur
• Metaverse Researcher/Analyst.
• Metaverse Developer/Programmer
• Metaverse Architect
• Metaverse Designer/Artist

The MSc in Metaverse is a research-based program that also equips students with the theoretical knowledge combined with the ability to apply this practically. Upon completion of the program, students can undertake further studies (PhD) in the field.

Term 1: Fall Term (September-December) courses

• MGA 676 – Design Theory and Methodology (4 ECTS) 
• MGA 674 – Research Methods (6 ECTS) 
• IFI7316.DT – Foundations of HCI (6 ECTS) 
• MGA 685 – Prototyping (4 ECTS)  
• MGA 671 – Interaction Design Methods (4 ECTS) 
• IFI7330.DT – Individual Subject (6 ECTS)

Term 2: Spring Term (January-June) modules

• IFI7329.DT – Universal Design (6 ECTS)
• IFI7160.DT – Current Topics in Human-Computer Interaction (4 ECTS)
• IFI7309.DT – Development of Interactive Systems (4 ECTS) 
• IFI7310.DT – User Experience Evaluation (4 ECTS)
• MGA 686 – Field Research Methods (4 ECTS)
• MGA 675 – Practice (6 ECTS)

Term 3: Fall Term (September-December) courses

• MGA 682 – Interaction Design Project (16 ECTS)
• IFI7328.DT – Master´s Thesis Seminar (16 ECTS)

Term 4: Spring Term (January-June) modules

• IFI7040.DT – Master’s Thesis (24 ECTS) 

The MSc in Interaction Design is a full-time and part-time postgraduate programme that equips its graduates with marketable skills in design, technology, and theory as related to the domain of Interaction Design, User Experience and Human-Computer Interaction.

Smart Systems

SEMESTER 1

• COMPUTER NETWORKS
• WEB ENGINEERING
• UBIQUITOUS COMPUTING

SEMESTER 2

• DISTRIBUTED AND CLOUD COMPUTING
• REASEARCH METHODOLOGY AND THESIS PLANNING
• SPECIALIZATION COURSE

SEMESTER 3

• MASTER THESIS
• SPECIALIZATION COURSE

Web Systems

SEMESTER 1

• COMPUTER NETWORKS
• WEB ENGINEERING
• UBIQUITOUS COMPUTING

SEMESTER 2

• DISTRIBUTED AND CLOUD COMPUTING
• REASEARCH METHODOLOGY AND THESIS PLANNING
• SPECIALIZATION COURSE

SEMESTER 3

• MASTER THESIS
• SPECIALIZATION COURSE

In the past decade, the developments experienced by the advancements of the Internet and the World Wide Web have been monumental for the Information Technology domain, as well as the society in general. Additionally, in recent years we have experienced an explosion of computational capabilities, not only from traditional computing machines (i.e. computers) but also from a wide variety of other devices such as mobile smart phones, tablets and several other autonomous smart devices. Furthermore, the developments in cloud computing and the integration of the whole spectrum of smart devices with the internet (Internet of Things) leads to the enchantment of existing information technology applications and to the creation of new areas of applications.

All these developments call for the existence of scientists and engineers that are adequately trained in the relevant technologies and have a deep knowledge of their interrelationships and the challenges that lie ahead.

The above realization constitutes the core motivation and forms the rationale behind the design and the development of the proposed program.

As its name implies, the program offers two specializations: (a) the Web Systems specialization, and (b) the Smart Systems specialization.

Aim of the Program:

The aim of the proposed program is to develop graduates that exhibit in-depth knowledge and advanced skills of the technologies relevant to web applications and smart systems. By the end of this program, graduates will master the knowledge required to design and implement efficient and effective solutions utilizing existing and emerging web and/or smart systems.

An equally important aim is that, through the program, the University will be able to strengthen its research activity in this fast evolving field and become a leading research institution in the area.

Specific Objectives

The main objectives of the program are to provide its graduates with in-depth knowledge and skills that will enable them to:

1. Master the methodologies, tools and technologies related to the development of web and smart systems, such as networking, web engineering, ubiquitous computing as well as distributed and cloud computing.
2. Demonstrate specialized knowledge and expertise in web systems with emphasis on human computer interaction and interactive system design, data mining, big data and analytics. (Web Systems Specialization only).
3. Demonstrate specialized knowledge and expertise in smart systems with emphasis on communications and security for smart systems, embedded systems, sensors and actuator technology for smart system applications. (Smart Systems Specialization only).
4. Work effectively as an individual, or within a team, in multi-disciplinary settings together with the capacity to undertake lifelong learning
5. Continue to study in a manner that may be largely self-directed and autonomous
6. Engage in research and communicate their findings and conclusions to specialists, and non-specialists clearly and unambiguously.

The language of instruction is English.

Key Learning Outcomes

Upon successful completion of this program, the students should be able to:

1. Master the methodologies, tools and technologies involved in the analysis, development and evaluation of web enabled applications and their interactions.
2. Master the methodologies, tools and technologies involved in the analysis, development and evaluation of applications of ubiquitous computing with emphasis on mobile devices, such as smart phones.
3. Exploit the underlying networking technologies that enable web and smart system applications, and demonstrate awareness on the recent networking developments and emerging technologies.
4. Recognize the role of cloud computing underlying technologies related to parallel and distributed computing, distinguish between the main cloud computing platforms and develop cloud based applications.
5. Critically evaluate various technologies and solution alternatives, within the context of web and smart systems, and identify the advantages and disadvantages of each.
6. Demonstrate the capacity to adapt to new technologies in the relevant fields and establish the connections and relations with existing ones
7. Communicate with other disciplines related in the field including engineering, business administration, graphic and web design.
8. Demonstrate awareness of the open challenges and research questions in the field.
9. Demonstrate the ability to understand and use technical literature and other information sources.
10. Conduct independent research in relevant fields, develop informed opinions and synthesize knowledge to report findings.
11. Think critically and reflectively on the capacity of the capabilities and limitations of data analysis and knowledge generation from distributed information systems.
12. Engage in critical thinking and problem solving in the specific domain of interest of the program

Specialization Specific Learning Outcomes (Web Systems):

Upon successful completion of this program, the students should be able to:

1. Gain sufficient theoretical knowledge and analytical skills to design and develop web and mobile applications using a structured approach.
2. Demonstrate an understanding on cutting edge web technologies and apply them for the development of advanced and complex web applications.
3. Extend critical awareness of the issues and challenges associated with ubiquitous computing, enhance the understanding on mobile systems and creatively design and develop mobile applications using various smartphone application development platforms.
4. Demonstrate an understanding on the theoretical dimension of human factors in the acceptance of computer interfaces and identify the impact of usable interfaces in the performance of mobile and web systems.
5. Evaluate and select the appropriate data mining methodology, where data mining is required or beneficial, for investigating practical web and mobile application challenges and critically analyse and evaluate the results.
6. Evaluate and select a systematic software reuse methodology in order to increase software productivity and improve software quality of an organization so as to successfully plan, manage, change and evolve any software project, for the development of applications on diverse platforms; desktop, mobile & web.
7. Identify sources of data, collect, and store data using appropriate big data related platforms, as well as process, analyse and summarize data to achieve breakthrough outcomes for organisations using data analytics methods.

Specialization Specific Learning Outcomes (Smart Systems):

Upon successful completion of this program, the students should be able to:

1. Design and develop smart system applications incorporating embedded systems and mobile devices as stand-alone systems or integrated with the web and the cloud.
2. Evaluate and select the appropriate embedded system technology (hardware and operate system) to meet specific strict requirements related to real time systems, fault tolerance and power consumption.
3. Integrate existing embedded system technology with custom designed systems using reconfigurable computing techniques and field programmable hardware (FPGAs).
4. Evaluate and select the appropriate sensors and actuators for smart system applications, to meet specific strict requirements. 
5. Evaluate and select the appropriate communication technology for smart system applications.
6. Demonstrate an understanding of the recent developments related to the Internet of Things (IoT), Machine-to-Machine (M2M) Communications, Smart Transportation Systems (STSs), and Vehicular Networks (VANETs) in Smart City Systems.
7. Assess the security concerns and impact that mobile and web systems intrinsically incorporate and argue on policies to alleviate them

Occupational Profiles of the Graduates

A large percentage of graduates of the MSc in Mobile and Web Systems program are expected to pursue careers in web application development and integration of applications with mobile devices, which is a rapidly growing section in organizations involved with software development. They are also likely to be employed in telecommunications companies, where a shift into the support of application-level services is present (see for example the establishment of CYTACOM by CYTA).

Graduates can also be employed in computer network related jobs and are also capable of obtaining employment in ICT departments of medium and large organizations and software houses.

The MSc in Web and Smart Systems is supported by the Mobile Device Laboratory (MDL)

Web Systems

SEMESTER 1

• COMPUTER NETWORKS
• WEB ENGINEERING
• UBIQUITOUS COMPUTING

SEMESTER 2

• DISTRIBUTED AND CLOUD COMPUTING
• MASTER THESIS I - PLANNING
• SPECIALIZATION COURSE

SEMESTER 3

• MASTER THESIS II
• SPECIALIZATION COURSE
   

Smart Systems

SEMESTER 1

• COMPUTER NETWORKS
• WEB ENGINEERING
• UBIQUITOUS COMPUTING

SEMESTER 2

• DISTRIBUTED AND CLOUD COMPUTING
• MASTER THESIS I - PLANNING
• SPECIALIZATION COURSE

SEMESTER 3

• MASTER THESIS II
• SPECIALIZATION COURSE

In the past decade and especially in the past few years during the COVID-19 global pandemic, the developments experienced by the advancements of the Internet and the World Wide Web have been monumental for the Information Technology domain, as well as the society in general. Additionally, in recent years we have experienced an explosion of computational capabilities, not only from traditional computing machines (i.e. computers) but also from a wide variety of other devices such as mobile smart phones, tablets and several other autonomous smart devices. Furthermore, the developments in cloud computing and the integration of the whole spectrum of smart devices with the internet (Internet of Things) leads to the enchantment of existing information technology applications and to the creation of new areas of applications.

All these developments call for the existence of scientists and engineers that are adequately trained in the relevant technologies and have a deep knowledge of their interrelationships and the challenges that lie ahead.

The above realization constitutes the core motivation and forms the rationale behind the design and the development of the proposed program.

Aim of the Program:

The aim of the proposed program is to develop graduates that exhibit in-depth knowledge and advanced skills of the technologies relevant to web applications and smart systems. By the end of this program, graduates will master the knowledge required to design and implement efficient and effective solutions utilizing existing and emerging web and/or smart systems.

An equally important aim is that, through the program, the University will be able to strengthen its research activity in this fast-evolving field and become a leading research institution in the area.

Objectives of the Program:

The main objectives of the program are to provide its graduates with in-depth knowledge and skills that will enable them to:

• Master the methodologies, tools and technologies related to the development of web and smart systems, such as networking, web engineering and ubiquitous computing.
• Demonstrate specialized knowledge and expertise in web and smart systems with emphasis on distributed and cloud computing, human computer interaction and interactive system design, data mining, big data analytics, communications of smart systems, embedded systems, smart sensors and actuators as well as artificial intelligence and IoT applications.
• Work effectively as an individual, or within a team, in multi-disciplinary settings together with the capacity to undertake lifelong learning.
• Continue to study in a manner that may be largely self-directed and autonomous.
• Engage in research and communicate their findings and conclusions to specialists, and non-specialists clearly and unambiguously

Key Learning Outcomes

Program Generic Learning Outcomes

1. Master the methodologies, tools and technologies involved in the analysis, development and evaluation of web enabled applications and their interactions.
2. Master the methodologies, tools and technologies involved in the analysis, development and evaluation of smart devices and systems.
3. Exploit the underlying networking technologies that enable web and smart system applications and demonstrate awareness on the recent networking developments and emerging technologies.
4. Recognize the role of cloud computing underlying technologies related to parallel and distributed computing, distinguish between the main cloud computing platforms and develop cloud-based applications.
5. Critically evaluate various technologies and solution alternatives, within the context of web and smart systems, and identify the advantages and disadvantages of each.
6. Demonstrate the capacity to adapt to new technologies in the relevant fields and establish the connections and relations with existing ones.
7. Think critically and reflectively on the capacity of the capabilities and limitations of data analysis and knowledge generation from distributed information systems.
8. Engage in critical thinking and problem solving in the specific domain of interest of the program.
9. Communicate with other disciplines related in the field including engineering, business administration, graphic and web design.
10. Demonstrate awareness of the open challenges and research questions in the field.
11. Demonstrate the ability to understand and use technical literature and other information sources.
12. Conduct independent research in relevant fields, develop informed opinions and synthesize knowledge to report findings.

Specialization Specific Learning Outcomes (Web Systems)

Upon successful completion of this program, the students should be able to:

1. Gain sufficient theoretical knowledge and analytical skills to design and develop web and mobile applications using a structured approach.
2. Demonstrate an understanding on cutting edge web technologies and apply them for the development of advanced and complex web applications.
3. Extend critical awareness of the issues and challenges associated with ubiquitous computing, enhance the understanding on mobile systems and creatively design and develop mobile applications using various smartphone application development platforms.
4. Demonstrate an understanding on the theoretical dimension of human factors in the acceptance of computer interfaces and identify the impact of usable interfaces in the performance of mobile and web systems.
5. Evaluate and select the appropriate data mining methodology, where data mining is required or beneficial, for investigating practical web and mobile application challenges and critically analyse and evaluate the results.
6. Evaluate and select a systematic software reuse methodology in order to increase software productivity and improve software quality of an organization so as to successfully plan, manage, change and evolve any software project, for the development of applications on diverse platforms; desktop, mobile & web.
7. Identify sources of data, collect, and store data using appropriate big data related platforms, as well as process, analyse and summarize data to achieve breakthrough outcomes for organisations using data analytics methods.

Specialization Specific Learning Outcomes (Smart Systems)

Upon successful completion of this program, the students should be able to:

1. Design and develop smart system applications incorporating embedded systems and mobile devices as stand-alone systems or integrated with the web and the cloud.
2. Evaluate and select the appropriate embedded system technology (hardware and operate system) to meet specific strict requirements related to real time systems, fault tolerance and power consumption.
3. Integrate existing embedded system technology with custom designed systems using reconfigurable computing techniques and field programmable hardware (FPGAs).
4. Evaluate and select the appropriate sensors and actuators for smart system applications, to meet specific strict requirements. 
5. Evaluate and select the appropriate communication technology for smart system applications. 
6. Demonstrate an understanding of the recent developments related to the Internet of Things (IoT), Machine-to-Machine (M2M) Communications, Smart Transportation Systems (STSs), and Vehicular Networks (VANETs) in Smart City Systems.
7. Assess the security concerns and impact that mobile and web systems intrinsically incorporate and argue on policies to alleviate them

Graduates’ employability prospects

The graduates of the Program have the knowledge and skills required for the design, implementation, maintenance and administration of web or smart systems related to their specialization.

Graduates of the program are expected to be employed both in and out the IT sector, such as software companies, ICT departments of medium and large organizations (private and public), research and innovation organizations, or work as independent consultants or developers. Jobs directly associated with this program include: application developer, web engineer/designer/developer, cloud engineer, software engineer, IT consultant, embedded and smart systems/solutions engineer/developer. The MSc in Web and Smart Systems also provide graduates the eligibility for scientific postgraduate doctoral level studies.