Overview

The MSc in Information and Communication Technology Systems Programme is being offered by the School of Science & Technology of the University Center of International Programmes of Studies of the International Hellenic University.

The programme aims to provide graduate level education and is targeted towards graduates who wish to broaden their knowledge in the field of Information and Communication Technology Systems and in contemporary inter-disciplinary issues arising between the areas of economy, energy and health which pertain to the improvement in the quality of life.

Information and Communication Technology (ICT) Systems have been a main driver of technological innovation during recent decades and now play a pivotal role in all aspects of modern life. Professionals who are experts in ICT Systems are therefore in constant demand. In order to really stand out in today’s job market ICT professionals need a combination of technical, managerial and interdisciplinary skills from different sectors of the economy, as well as exposure to an international environment.

The International Hellenic University (IHU) offers just such a highly diverse graduate programme. In a fully English-speaking environment, our MSc in ICT Systems students learn to excel in their technical skills while also acquiring grounding in managerial skills as these apply in a number of different areas including healthcare, the financial sector and the green economy. The lecture series by leading academic instructors from Greece and abroad, together with projects and dissertation work, mean that students graduate well equipped and highly competitive at international level.

This programme is designed for those University graduates of Informatics/Computer ScienceElectrical Engineering and also Natural Sciences departments, who wish to acquire a competitive edge in the rapidly converging information and telecommunication technologies market.

The courses of the programme are taught exclusively in English. The academic staff comes from Universities in Greece and abroad.

Official Government Gazette:

Key facts
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Start date: October 2023

Application deadline extension:  30 September 2023 or until places are filled or until places are filled

Campus: Thermi, Thessaloniki

Duration/Mode: 18 months (full-time) or 30 months (part-time)/(available also in distance learning mode)/weekdays evenings

Taught language: English

Entry requirements: An undergraduate degree from an accredited University

Language requirements: English language knowledge documented with a relevant certificate, corresponding at least to the State Certificate of Language Learning Level B2 or other certificate proving good knowledge of English. Holders of an undergraduate or postgraduate degree at a Foreign University in English are exempt from this obligation.

Fees: 2,900€ (total)

How to apply: Programme announcement- 2nd Phase of Admission of Graduate Students (en+gr

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Who can apply

To be considered for the programme, candidates are required to have:

  • an undergraduate degree from a recognized University
  • English language knowledge documented with a relevant certificate, corresponding at least to the State Certificate of Language Learning Level B2 or other certificate proving good knowledge of English. Holders of an undergraduate or postgraduate degree at a Foreign University in English are exempt from this obligation.

Course content

During the first term, all students are required to attend five mandatory core courses. During the second term, all students follow a further three required courses and a combination of two elective courses. Finally, during the third term, work is dedicated exclusively to the Master’s dissertation.

The core courses

1st Term Core Courses During the first term, all MSc in ICT Systems students attend five (5) mandatory core courses that provide a thorough grounding in key functional areas of the ICT sector. These core courses sum up to a total of 30 ECTS units.

Instructor(s):Prof. V. Peristeras
Teaching Hours and Credit Allocation:30 Hours, 6 Credits
Course Assessment:Exam & Coursework

Aims

The purpose of this course is to provide a broad understanding of the importance of ICT systems in the modern business environment so that the management makes the right decisions on issues relating to information systems. The course focuses on issues of information systems integration within the organization, information systems utilization according to the organization’s capabilities and its implications on processes and individuals, as well as information resources management. Topics covered include process analysis, project analysis, production planning and scheduling, ICT systems and new business models, quality management, supply chain management, capacity and facilities planning. The course also develops basic macroeconomic theory to enable managers to critically evaluate economic forecasts and policy recommendations and then applies these concepts in a series of case studies.

Learning Outcomes

Upon completing this course, students will:

  • Develop analytical skills in planning, evaluating and supervising a project in ICT
  • Develop skills in Evaluating and Sustaining Production Quality in ICT
  • Understand some basic elements of Supply Chain Management
  • Develop skills in Human Resource and Workforce allocation and management
  • Broaden their experience through several case study examples

Content

  • Process and Project Analysis
  • Production Planning and Scheduling
  • Quality Management
  • ICT Systems and New Business Models; E-Commerce, Decision Making
  • Capacity and Facilities planning
  • Workforce Scheduling
  • Project Valuation and Financing
  • Case Studies

Reading

  • E. Turban, L. Volonino, Information Technology for Management, 8th Edition, 2010, John Wiley & Sons, Inc.
  • Oz E. Management Information Systems, Course Technology, 6th edition.
  • J. Laudon, K. Laudon, Essentials of Management Information Systems, Prentice Hall, 8th edition.
  • M.H. Sherif, Managing Projects in Telecommunication Services, Wiley-IEEE Press.

Instructor(s):Dr. A. Ampatzoglou, Dr. I. Magnisalis
Teaching Hours and Credit Allocation:30 Hours, 6 Credits
Course Assessment:Exam & Coursework

Aims

The students will get acquainted with all modern tools and principles of modern Web Information Systems through this course. An introduction will be given to basic internet protocols and applications and the course will guide the students in more advanced web architectures and implementation using modern programming language tools and security implementations.

Learning Outcomes

On completion of the course students will be able to:

  • Understand the principal protocols, architectures and standards for Internet and Web applications
  • Develop simple Web applications, using modern tools of Java, XML and PHP
  • Incorporate commonly used security protocols (SSL, HTTPS) in their information system design
  • Adapt their web design to enhance reliability, efficiency and internationalisation
  • Understand the basic principles and future directions of Web 2.0

Content

  • Internet and the Web protocols and standards.
  • Architecture and Components of Web-Based Applications (3-tier and multi-tier Client/Server systems, Web servers, Database servers).
  • Design and implementation of applications on the Internet environment with the use of modern tools (Java technology, XML, PHP etc).
  • Advanced Design Issues (Efficiency, Reliability, and Internationalisation).
  • Security / encryption protocols (SSL, HTTPS). Web 2.0.

Reading

  • Taniar D., Rahayu J. W. (2004) Web information systems Hershey, PA: Idea Group Publishing.
  • Vidgen R., Avison D., Wood B., Wood-Harper T. (2002) Developing Web Information Systems: From Strategy to Implementation, Butterworth-Heinemann Information Systems Series, Elsevier.
  • M. Stepp, J. Miller, V. Kirst (2012) Web Programming Step-by-Step, Step-By-Step Publishing

Teaching Hours and Credit Allocation:30 Hours, 6 Credits
Course Assessment:Exam & Coursework

Aims

This course will examine computer networks within the context of the Internet. We will study the fundamental principles, elements, and protocols of computer networks. We will investigate how the different protocols work, why they work that way, and their performance trade-offs. Using this knowledge, we will try to examine the way applications are deployed on the Internet and their performance trade-offs. In particular, we will try to examine some strategies that are commonly used to accelerate application level performance in the context of the operation of the Internet.

Learning Outcomes

On completing the course students will be able to:

  • Explain the operation of a range of computer networking applications such as email, web, and peer-to-peer file-sharing
  • Relate the architecture of the Internet to the underlying design principles
  • Illustrate the operation of common routing protocols, queuing mechanisms, and congestion control mechanisms
  • Develop elements of a network such as gateways and routers that conform to IETF standards with acceptable levels of simplification
  • Explain the performance of a given set of routing protocols, queuing mechanisms, and congestion control mechanisms on an example network.

Content

  • Introduction to Computer Networks
  • Sockets Programming
  • Protocol Stacks and Layering: Application Layer, Physical Layer, Link Layer Basics.
  • Switching & Flow Control
  • Ethernet and Bridging
  • IP forwarding & addressing
  • IP Packets & Routers
  • Routing: RIP & OSPF, Routing: BGP, Multicast, DNS, IPv6, tunnelling, NAT, VPN, Virtual circuits, ATM, MPLS, Transport Intro.
  • TCP & Congestion Control.
  • TCP Performance
  • Multimedia/QoS, QoS & Mobile (IP & TCP)
  • Ad-hoc networks
  • Web + CDNs + Caching, P2P
  • Security – SSL, Security – firewalls, DoS
  • Broadband access networks (xDSL,UWB, DOCSIS)

Instructor(s): Prof. C. Tjortjis
Teaching Hours and Credit Allocation: 30 Hours, 6 Credits
Course Assessment: Exam & Coursework

Aims

The course aims to familiarise students with contemporary database systems, as well as emerging database technologies. It discusses basic aspects of advanced database techniques and exposes tools and technologies that can be used along with “core” database systems. Students are expected to engage in practical database system design through a series of assignments and coursework. The emphasis in the lectures will be on general concepts and theoretical foundations. In addition to the theoretical concepts, the course will require students to use commercial database systems and develop a class project.

Learning Outcomes

  • On completing the course, students will be able to:
  • Develop the logical model of a relational database.
  • Use essential SQL tools to program DB systems.
  • Understand advanced concepts of DM management and architecture.
  • Organize, store and process data efficiently, using contemporary technologies such as Data Warehouses.
  • Understand and apply various emerging technologies, including Data Mining, OLAP, Information Retrieval, and Search engines.
  • Understand and utilise knowledge extracted from large volumes of data.

Content

  • ER model, relational model.
  • SQL.
  • Indexing.
  • Query processing and optimization.
  • Data warehousing and OLAP.
  • Data Mining and Business Intelligence.
  • Information Retrieval.
  • Web Search.

Reading

  • Elmasri R., Navathe S. B., (2010), Fundamentals of Database Systems: Global Edition, 6th Edition, Pearson.
  • Garcia-Molina H., Ullman J., and Widom J., (2009), Database Systems: The Complete Book, 2nd edition, Pearson.
  • Silberschatz A., Korth H., and Sudarshan S., (2010), Database System Concepts, 6th Edition, McGraw-Hill.
  • Ramakrishnan R, Gehrke J. (2002), Database Management Systems, 3rd edition, McGraw-Hill Science/Engineering/Math.

Teaching Hours and Credit Allocation:30 Hours, 6 Credits
Course Assessment:Exam & Coursework

Aims

This course provides an introduction to the foundational aspects of cybersecurity and computer security. Most modern organisations face security and privacy risks that threaten their valuable assets. It is imperative to design secure and privacy-aware information systems that protect against these threats. This course provides a wide range of skills and knowledge of existing technologies, security and privacy principles to develop the professional skills and experience needed for information systems security.

Learning Outcomes

On completing the course students will be able to:

  • Develop the knowledge, understanding and skills to work as a computing security professional
  • Learn the concepts, principles, techniques and methodologies you need to design and assess complex networks, systems and applications
  • Develop the practical experience you need to plan, perform and direct security audits of information systems to the level required by standard security frameworks
  • Develop the appropriate legal and ethical skills you need to be a security professional.

Content

  • Information security –Security Policy
  • Identification -Authentication
  • Authorization –Access Control –Auditing -Accountability
  • Malicious Attacks-Malware
  • Hash Functions -Digital Signatures Public Key Infrastructure (PKI) -Digital Certificates
  • Firewalls
  • ISO 27001
  • Application Security

2nd Term Core Courses During the second term, all students are initially required to attend three (3) required courses which give a total of 18 ECTS.

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Instructor(s):Professor Periklis Chatzimisios
Teaching Hours and Credit Allocation:30 Hours, 6 Credits
Course Assessment:Exam & Coursework

Aims

The course aims at studying fundamental principles of current and forthcoming mobile and wireless networks. Building on the knowledge gained during the 1st term course on Computer Networks, it analyzes how the basic networking operations are affected by the additional challenges of mobile and wireless environments but also the particularities of novel networking paradigms that are currently in the phase of research or initial/experimental deployments. Hence, the course covers cellular networks (mobile macrocellular and local area ones), but also more distributed and user-driven networking and service paradigms such as wireless multihop and opportunistic networks, as well as participatory sensing and mobile crowdsensing.

Learning Outcomes

By successfully completing the course students are expected to have:

  • understood the particular challenges that wireless and mobile (distributed) environments place on basic networking operations
  • gained knowledge about fundamental design principles (e.g., cellular architecture, mobility management) that address these challenges and developped basic network design skills
  • familiarized themselves with different cellular communication technologies and standards (3G, LTE, WLANs) for engineering mobile cellular networks
  • developped a good a understanding of novel, highly distributed, wireless networking paradigms such as wireless ad hoc networks and opportunistic networks and the way networking is realized over them
  • been exposed to the latest trends in the area of participatory sensing and mobile crowdsensing, which combine the power of the crowdsourcing principle with the growing functionality of smart mobile devices

Content

  • Challenges for the operation of mobile and wireless networks
    • user/device mobility, wireless environment
  • Fundamental principles of mobile cellular networks:
    • cellular architecture (frequency reuse, sectoring, capacity vs. coverage)
    • mobility management (macro- and micro-mobility, handovers), location management
  • Current cellular systems and standards:
    • GSM/GPRS, 3G, LTE, WLANs
  • Network-, transport- and application-layer adaptations for wireless environments
    • Mobile IP, TCP enhancements, proxies
  • Wireless multihop and ad hoc networks
    • additional challenges due to their distributed operation
    • routing metrics (ETX, WCETT) and routing protocol (DSDV, DSR, OLSR) solutions and tradeoffs
    • transport solutions (non TCP solutions, hop-by-hop)
  • Opportunistic networking (Delay Tolerant Networks)
    • the store-carry-and-forward principle, intermittently connected networks
    • forwarding and routing under deterministic mobility (controlled flooding vs. utility-based and socioaware approaches)
  • Participatory networking and mobile crowdsensing
    • smart spaces and pervasive computing
    • sensor/smartphone selection, incentive provision, applications

Reading

Schiller J. (2003) Mobile Communications, Addison Wesley, 2nd edition.

Teaching Hours and Credit Allocation:30 Hours, 6 Credits
Course Assessment:Exam & Coursework

Aims

The ever growing penetration of computers in everyday life has led to the need to develop a vast number of software programs, which in turn resulted to the emergence of a large number of programming languages, frameworks, SDKs, paradigms and techniques. Being able to write functional and maintainable code entails good knowledge of the most important programming concepts, methodologies and techniques. This is even more necessary now because of the extended fragmentation of the programming market. This course aims to teach students popular principles, techniques, tools and methods used to develop software efficiently. Requirement analysis, UML, Object-oriented analysis, design and programming, usage of Application Programming Interfaces (APIs), software maintenance, project and version management are some of the topics covered through theory and practice.

Learning Outcomes

On completing the course students will be able to:

  • Appreciate principles, concepts, and techniques used to develop software efficiently
  • Demonstrate how to effectively apply software engineering methods, tools and techniques
  • Plan, manage and collaborate on a Software Development group project
  • Obtain the knowledge and skills required for effective management of the software maintenance process
  • Have developed effective software engineering, management and communication skills

Content

  • Software development principles, techniques, methods and tools
  • Requirement analysis
  • UML
  • Object-oriented analysis, design and programming
  • Application Programming Interfaces (APIs)
  • Software maintenance and evolution
  • Project and version management

Instructor:Prof. Bozanis
Teaching Hours and Credit Allocation:30 Hours, 6 Credits
Course Assessment:Exam & Coursework

Aims

The big data explosion has led to new computing paradigms, the most prevalent among them being cloud computing. Cloud computing is about vast computing resources on demand, that allow for centralized data storage and online access. Big data is a broad term that includes several concepts and tasks, such as data capture, storage, sharing, management and analysis. This course focuses mostly on the big data storage and management part, rather than the analysis as well as cloud service models, architectures and tools. Students will familiarize with modern big data and cloud technologies, understand the privacy and security concerns and learn about popular big data and cloud computing platforms.

Learning Outcomes

On completing the course, students will be able to:

  • Develop the knowledge, understanding and skills to work with Big Data.
  • Deploy a structured lifecycle approach to data analytics problems.
  • Apply appropriate analytic techniques and tools to analyzing big data.
  • Understand Cloud Computing Concepts and Mechanisms.
  • Learn the concepts, principles, techniques and methodologies you need to manage cloud services and resources.

Content

  • Big data concepts, principles and practical applications.
  • Big data capture, storage, sharing, management and analysis.
  • Cloud Computing Concepts and Mechanisms.
  • Cloud Architectures.
  • Working with Clouds.
  • Managing Cloud Services and Resources.
  • Big Data and cloud computing platforms.

Reading

  • T. Erl, R. Puttini, Z. Mahmood, Cloud Computing: Concepts, Technology & Architecture, Pearson, 2013.
  • EMC Education Services (Editor), Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data, Wiley 2015.

In addition to these required courses, during the second term, students tailor the programme further to their own needs by choosing two elective courses, which give a total of 12 ECTS.

The elective courses

During the second term students tailor their programme further by choosing elective courses. The choice of elective courses must sum up to 12 ECTS (2 courses). Some of the elective courses may not be offered in a particular year, depending entirely on student demand. 2nd Term Elective Courses

Instructor:  Prof. Panagiotis Bozanis
Teaching Hours and Credit Allocation:   30 Hours, 6 Credits
Course Assessment:  Exam & Coursework

Aims

The course covers the basic principles and techniques of information retrieval, which is the process by which a computer system can respond to a query about a given topic. A successful and meaningful response requires efficient data organization and classification, as well as efficient indexing and clustering algorithms. The students will study all aspects of data organization and processing that allow for efficient information retrieval as well as the underlying computational models and tools.

Learning Outcomes

On completing the course, users will be able to:

  • Understand key concepts of information retrieval techniques and be able to apply these concepts into practice.
  • Apply information retrieval principles to locate relevant information in large collections of data.
  • Understand and deploy efficient techniques for the indexing of document objects that are to be retrieved.
  • Implement features of retrieval systems for web-based and other search tasks.
  • Analyse the performance of retrieval systems.

Content

  • Introduction to information retrieval.
  • Retrieval Models.
  • Dictionaries, term vocabulary and postings lists.
  • Index construction and compression.
  • Vector space model and classification.
  • Support vector machines and machine learning on documents.
  • Search systems.
  • Latent semantic indexing.
  • Link analysis.
  • Evaluation.

Reading

  • C.D. Manning, P. Raghavan and H. Schütze (2008), Introduction to Information Retrieval, Cambridge University Press.
  • S. Büttcher, C.L. A. Clarke and G.V. Cormack (20016), Information Retrieval, Implementing and Evaluating Search Engines, MIT Press.
  • Grossman, D.A., Frieder, O. (2004), Information Retrieval, Algorithms and Heuristics, Springer.

Teaching Hours and Credit Allocation:30 Hours, 6 Credits
Course Assessment:Exam & Coursework

Aims

This course examines basic concepts of Knowledge and Knowledge Management, placing emphasis on knowledge encountered in the Web. At first, it briefly deals with the notion of knowledge and its sources, the architecture and life cycle of knowledge management systems, how knowledge is captured, and how knowledge is formally represented using various formalisms. The core theme of the course covers extensively information and knowledge representation and interchange technologies in the Web, such as information representation using XML, information processing using XPath/XSLT, metadata representation using RDF, vocabulary descriptions using RDF Schema, and finally, knowledge representation in the web, using ontologies (OWL), and rules (SWRL, OWL2 RL, RIF). During the course various knowledge management web systems and tools are demonstrated and practised.

Learning Outcomes

On completing the course, students will be able to:

  • acquire essentials skills on Knowledge Management Systems
  • comprehend web Knowledge Management languages and technologies, including XML, XPath, XSLT, RDF, RDFS, OWL
  • use Knowledge Management systems through selected assignments.

Content

  • Basic concepts of Knowledge and Knowledge Management.
  • Knowledge modeling: Ontologies and Linked Data.
  • Representation languages (XML, RDF, RDF Schema, OWL, SPARQL).
  • Web services (SOAP, JSON, OWL-S).
  • Demonstration and practice of various web Knowledge Management systems (e.g., Protégé, Google Knowledge Graph).

Instructor(s): Prof. C. Tjortjis
Teaching Hours and Credit Allocation:   30 Hours, 6 Credits
Course Assessment:  Exam & Coursework

Aims

The course covers Knowledge Discovery in Databases (KDD) and Data Mining (DM) as a set of computational tools and technologies, which provide valuable assistance for business analysis and strategic business decision making. This is a hands-on course that provides an understanding of the key methods of data visualization, exploration, classification, prediction, and clustering. Students will learn how to apply various data mining techniques for solving practical problems and how to develop and use simple business analytics systems.

Learning Outcomes

On completing the course, students will be able to:

  • Organise and efficiently process any knowledge, either given a priori or extracted
  • Understand the basic concepts of data mining
  • Understand and apply various data mining approaches, including Classification, Clustering and Association Rules.
  • Understand, evaluate and utilise knowledge extracted from large volumes of data.

Content

  • Introduction to Knowledge Discovery in Databases (KDD) and Data Mining (DM).
  • Classification.
  • Clustering.
  • Association Rules.
  • DM Systems, Data pre-processing and Evaluation.

Reading

  • J. Han and M. Kamber, Data Mining: Concepts and Techniques, 3rd ed., The Morgan Kaufmann Series in Data Management Systems, Morgan Kaufmann Publishers, 2011.
  • I. Witten, E. Frank, and M. Hall, “Data Mining: Practical Machine Learning Tools and Techniques”, 3rd Ed., Morgan Kaufmann, 2011.
  • J. Ledolter, Data Mining and Business Analytics with R, Wiley, 2013.
  • P.N. Tan, M. Steinbach, and V. Kumar, “Introduction to Data Mining” Int’l Ed., 1/e, Pearson Higher Education, 2006.
  • R. Sharda, D. Delen, E. Turban, Decision Support and Business Intelligence Systems Int’l Ed. 10/E, Pearson Higher Education, 2015.
  • M.H. Dunham, “Data Mining: Introductory and Advanced Topics”, Prentice Hall, 2003.
  • M.M. Gaber (ed.), Journeys to data mining: experiences from 15 renowned researchers, Springer, 2012.

Instructor(s):Prof. V. Peristeras
Teaching Hours and Credit Allocation:30 Hours, 6 Credits
Course Assessment:Exam & Coursework

Aims

The aim of this course is to broaden and expand knowledge of the concepts and techniques required for the design, operation and control of the modern upcoming e-commerce applications and e-government systems that are massively introduced by western governments to fight bureaucracy. The essential computing background to support such systems is presented, along with the individual requirements for a wide variety of modern life activities that can be performed online.

Learning Outcomes

On completing the course students will:

  • Develop knowledge of the information and communication skills to support and develop this type of information systems
  • Broaden their knowledge into e-commerce, covering business, marketing, organisational and payment security issues
  • Explain the concepts, processes behind developing an e-learning facility
  • Understand the technological, ethical, legal and practical requirements of an electronic government information system

Content

  • Current and emerging business models
  • The use of information and communications technology
  • Mobile commerce
  • E-marketing and e-business strategy
  • E-consumer behaviour and advertisement
  • Organisational and managerial challenges in the electronic environment
  • E-Payment systems
  • E-learning; security issues and the legal environment
  • Understanding eGovernment
  • eAdministration/G2G
  • eCitizens/ eAccountability
  • eDemocracy/eParticipation
  • eServices/G2C & G2B
  • Legislation for eGovernment
  • Integrated eGovernment, Group Presentations

Reading

Laudon K., Guercio-Traver C. (2008) E-Commerce 2009: Business, Technology, Society, Prentice Hall, 5th edition.

Turban E., Lee J. K., King D., McKay J., Marshall P., (2008) Electronic Commerce 2008, Prentice Hall. Abramson M., Morin T. (2003) E-Government 2003, Rowman & Littlefield, Lanham, MD.

Heeks R. B. (2006) Implementing and Managing eGovernment: An International Text, Sage Publications, London

Teaching Hours and Credit Allocation:30 Hours, 6 Credits
Course Assessment:Exam & Coursework

Aims

Mobile computing has recently emerged with the spread of smartphones and it has soon become the fastest growing ICT field. A significant percentage of businesses and organizations are already marketing their products and services through mobile sites and applications and those who haven’t already, they will have to do so in the near future. This course introduces the students to the basic concepts of mobile computing technologies as well as business principles and practices in order to exploit the full potential of the mobile application market. The students will learn how to imbue a business strategy with capabilities and functionalities offered by the new technological platform.

Learning Outcomes

Students will be able to:

  • Learn basic principles of marketing and B2B of mobile computing
  • Harness the potential that mobile computing offers to businesses
  • Learn about the technologies involved (wireless and mobile communications, web application development basics, security protocols involved, etc.)
  • Identify strengths, weaknesses, risks and opportunities and build a successful strategy

Content

  • Wireless technologies (Wi-Fi, 3G, 4G etc.)
  • Cross-platform mobile web applications
  • Native mobile applications that exploit the device’s hardware
  • Designing a mobile computing business strategy and evaluating risks and opportunities
  • Social networks for collaboration and marketing
  • Security and privacy aspects
  • Case studies

Reading

Mobile Design and Development: Practical Concepts and Techniques for Creating Mobile Sites and Web Apps, Brian Fling, O’Reilly Media Inc., 2009, ISBN 0596155441, 9780596155445.

Handbook of research in mobile business: technical, methodological, and social perspectives, Bhuvan Unhelkar, 2nd Edition, Vol.1 & 2, Idea Group Inc (IGI), 2009, ISBN1605661562, 9781605661568.

Hours and Credit Allocation:  30 Hours, 6 Credits
Course Assessment:  Exam & Coursework

Learning outcomes

On completing the course, students will be able to:

  • Develop knowledge of embedded system & sensor networks.
  • Acquire a solid overview of the forthcoming technologies in the Internet of Things.
  • Understand the challenged faced by IoT devices in various application domains.
  • Familiarize with different technologies and standards.

Content

  • Embedded systems and real-time operating systems.
  • Programming languages for embedded systems.
  • Sensor networking and technologies.
  • Mobile sensing systems.
  • Smart grid & Intelligent Transportation Systems.

Credit Allocation:6 Credits
Course Assessment:Final deliverable

Aims

The Consulting Project will require students to apply knowledge gained in classroom into practice. Students will tackle real-life problems and challenges facing companies or organisations in order to provide actual business solutions. Following a procedure of specifications/requirements, design and implementation, students will prepare and present their concrete and practical solutions in a final deliverable report.

Learning Outcomes

On completing the course, students will be able to:

  • Understand real-world problem faced by companies/firms and propose functional solutions.
  • Develop critical thinking and ability to integrate data and information towards the optimal solution.
  • Understand the structure, operational mode and challenges of real-world companies.

Content

  • Understanding and recording a company’s needs and challenges.
  • Project requirements.
  • Data analysis, implementation and company feedback.
  • Producing a deliverable.

The Dissertation

During the third term, students work on their Masters Dissertation project, the thematic area of which is relevant to their programme of studies and their interests. The dissertation provides a good opportunity to apply theory and concepts learned in different courses to a real-world ICT problem or challenge. Students are supervised throughout their projects by a member of the academic faculty and the academic associates. After submission of the dissertation, students present their projects to classmates and faculty at a special event.

Duration of studies

The duration of the full-time study programme in order to obtain the MA degree is three (3) academic semesters. For students who so wish, there is also the possibility, upon request, of attending the programme on a part–time basis. In this case, the duration of the MA will be five (5) academic semesters. Lectures mainly take place on weekday evenings. The programme is also available through distance learning. Distance Learning teaching methods involve: (a) Face-to-face or classroom based learning: Students will be required to be physically present at the University for a weekend at the beginning of each semester (b) Synchronous learning: Student will have to attend remotely the classes which will be held regularly during each semester, weekday afternoons (about 2-4 times per week depending on the mode, always after 17:00) and possible Saturday morning  (c) Asynchronous learning: Students will use online learning resources and will be assessed through a variety of diagnostic tools and formative assessment techniques (d) Summative assessment: Students will be typically required to be physically present at the University for the final exams at the end of each semester.

The Academic Faculty

Faculty Members

Dr Christos Tjortjis Dr Christos Tjortjis Associate Professor
Dean of the School
+30 2310 807576
c.tjortjis@ihu.edu.gr
Dr Maria Drakaki Professor Maria Drakaki
Deputy Dean of the School
+30 2310 807524
mdrakaki@ihu.gr
Professor Panayiotis Bozanis Professor Panayiotis Bozanis
+30 2310 807501
pbozanis@ihu.gr
Dr Eleni Heracleous Dr Eleni Heracleous
Associate Professor
e.heracleous@ihu.edu.gr
Dr Vassilios Peristeras Dr Vassilios Peristeras Associate Professor
+30 2310 807539
v.peristeras@ihu.edu.gr
Dr D.Tzetzis Dr Dimitrios Tzetzis Associate Professor
+30 2310 807548
d.tzetzis@ihu.edu.gr
Dr D.Tzetzis Dr Spiros Papakostas Assistant Professor
spapakostas@ihu.edu.gr

Other Research and Teaching Personnel

Dr Christos Berberidis Dr Christos Berberidis Research and Teaching Staff +30 2310 807534 c.berberidis@ihu.edu.gr
Dr Dimitrios Baltatzis Dr Dimitrios Baltatzis Research and Teaching Staff d.baltatzis@ihu.edu.gr
Dr Georgios Martinopoulos Dr Georgios Martinopoulos Academic Associate +30 2310 807533 g.martinopoulos@ihu.edu.gr
Image not available Dr Leonidas Akritidis Academic Associate
Image not available Dr Dimitrios Karapiperis Academic Associate
Image not available Dr Paraskevas Koukaras Academic Associate
Image not available Dr Nikolaos Serketzis Academic Associate
Image not available Dr Katerina Tzafilkou Academic Associate

Visiting Faculty

  • Prof. Konstantinos Rantos
  • As. Prof. Anastasios Politis
  • Dr Ioannis Magnisalis
  • Prof. Panagiotis Tzionas
  • Prof. Periklis Chatzimisios
  • Prof. Nikolaos Bassiliades
  • Prof. Stavros Stavrinides

Fees & Financing

Fees

The programme fees for the MSc in ICT Systems is 2900€. The amount is payable in two instalments for the full time mode or in four instalments for the part time mode at the beginning of each semester. The fees are also eligible for financing through LAEK 0,45% – OAED programme.

Deposits

If you have been accepted to a postgraduate programme, you will need to make a payment of the deposit of 500 Euros to secure your place. This amount will count towards the first instalment of your tuition fees. The deposit is non-refundable once you have commenced your studies at the IHU. Prior to that, a refund can be made but a 20% administrative fee will be retained. The deposit can be paid by bank transfer or bank draft. Credit card payments can be made through electronic banking (contact your Bank as handling fees may apply).

Scholarships

The School of Science & Technology offers a number of scholarships for the programmes it offers, covering a significant proportion of the fees. These scholarships are competitive. Award criteria include the quality of the first degree, the undergraduate grades of the candidate, his/her command of the English language and overall profile. Candidates for scholarships should include a separate letter with their application documents in which they request to be considered for a scholarship, stating the reasons why they think they qualify.

Programme announcement – Admissions

Next MSc in ICT Systems class starts in October 2023. The application deadline for the MSc programme has been extended. Interested parties are invited to submit their application from July 1st, 2023 to September 30th, 2023 or until places are filled, by following instructions at the application page.

Ideal Career path

More than 70% of our graduates end up in good, relevant jobs within a year from graduation. A multitude of employment opportunities are envisaged for graduates of the MSc in ICT Systems programme. Indicatively they include:

  • Managerial, technical and research positions in IT departments and IT companies
  • Banking and other Financial Institutions
  • Multinational Corporations and Small and Medium Enterprises (SMEs)
  • e-Commerce and Health software companies
  • Mobile network providers and broadband Internet providers
  • Sensor networks and telematics companies
  • Multimedia content providers and developers (Digital Radio, Television providers and Media)
  • Governmental Telecommunication Regulatory Authorities

In addition to technical skills gained through study, our students benefit from the University’s excellent Careers Office in order to attain essential soft skills (e.g. communication skills, interview preparation, CV writing etc.) to better prepare for the job market.

Location

The MSc in ICT Systems takes place in the facilities of the School of Science & Technology of the University Center of International Programmes of Studies of the International Hellenic University in Thermi-Thessaloniki.

Contact

Postal address: School of Science & Technology Department of School of Science & Technology University Center of International Programmes of Studies 14th km Thessaloniki – Nea Moudania 570 01 Thermi, Thessaloniki, Greece Tel: +30 2310 807 529 Email: : infotech@ihu.edu.gr