7th Semester

In the 7th semester, students beyond the final year project shall choose:
• one (of the two) compulsory courses of the secondary major (CSM) of the (main) Major that they have choosed and
• three optional courses (Opt) through the list of the available courses of all majors.

Clarification instructions for Curriculum about students that are in the 4th year of their studies (IDs E/14... and older)

Core

DS-906 Final Year Project [C] Member of faculty

  • Course Code DS-906 Type of Course Core
  • Theory/Lab Sessions - ECTS Credits 5
  • Semester 7th Semester FacultyMember of faculty

The final year project is carried out under the supervision of one of the faculty members and involves – at a first stage – the identification of the subject/ technological problem to be addressed and  the associated data collection. The output of the project, namely the description of the problem formulation, the solution definition and implementation and the illustration of results and final conclusions, is presented in the final year project thesis.

The final year project aims to

  • Exercise and extend the student’s academic skills, by enabling in depth understanding of the context of (a part of) a discipline. This may be achieved by exploiting particular skills or knowledge acquired from taught courses.
  • Exercise and extend professional skills by testing the student’s ability to research, organise, report and present the results if his/her work and develop initiative and independent thinking.
More »

MAJOR IN "COMMUNICATIONS & NETWORKS"

Secondary Major in "TELECOMMUNICATIONS": Compulsory Courses

DS-303 Satellite Communications [CSM/TEL] A. Kanatas

Learning Outcomes

The course provides the basic principles of cellular mobile communication systems. It also provides the methodologies of analysis and design of these systems. By concluding the course, students are able to analyze and design basic mobile communication systems by emphasizing in physical layer techniques. Specifically, students may recognize, describe and distinguish the characteristics of several type of cells, communication channels and multiple access techniques.

Moreover, ingredient components of a cellular system are described, and students are able to analyze and design systems with different requirements of telecommunication traffic and quality links. The analysis and design are based on the identification of several criteria, on the computation of thresholds of performance of links, on the comparison of alternative implementation plans and on the evaluation of the total performance of digital systems.

The lab sessions aim to provide a deeper understanding of physical phenomena of propagation in the wireless channel and the simulation of cellular systems.

Course Contents

  • Initially, basic concepts of Mobile Communications Radiosystems are provided (cell types, communication channel types, basic cellular system operations).
  • Next, the basic Network Access Techniques (Multiple Access Techniques, Random Access Techniques) are discussed.
  • Also, reference is made to the evolution of Wireless Communication Systems (1st, 2nd, 3rd, and 4th generation cellular systems, Wireless Telephony Systems, Paging Systems, WLANs, WPANs, PMRs).
  • Students are introduced to the concept of cells and frequency reuse (elements from regular hexagon geometry, cellular systems design).
  • Then the basic concepts of telecommunication traffic analysis and systems performance is provided (elements of Queuing Theory, Erlang B model, Erlang C model, spectral performance of cellular systems).
  • In the following the main wireless propagation mechanisms are presented (multipath propagation, Doppler fading and shift, propagation loss, shadowing, coverage area definition, radio channel capacity limits).
  • Also, interference types (co-channel interference and noise, neighboring channel interference) as well as handover and performance techniques (categorization of handover techniques, advantages and disadvantages of techniques, stable performance, dynamic performance, elastic performance) are discussed and compared.
  • Then techniques for improving spectral efficiency (sectoring, cell splitting) are analyzed.
  • Finally, elements and techniques of physical layer design (modulation and coding techniques, co-channel interference mitigation techniques) are presented and a presentation of standardized Mobile Communications Systems (GSM, GPRS, 3G and 4G) is presented.
  • In addition, extra content (in evdoxos.ds.unipi.gr) like articles, audiovisual lectures and Internet addresses, as well as exercises for student’s practice are posted electronically.
  • Case studies, exemplary problems and methods for solving them are presented.
More »

Secondary Major in "NETWORKS": Compulsory Courses

DS-331 Design and Optimization of Networks [CSM/NET] A. Rouskas

Learning Outcomes

This course targets on the design, evaluation and optimization of networks and services. The course is following the approach of top-down network design, that is most commonly encountered on medium to large scale networking projects. At the end of the course the students will be able to understand and evaluate alternative design options at every stage of data networks design, including requirement and specification definition, logical and physical design, selection of appropriate technologies and protocols, implementation, testing and optimization.

Course Contents

  • Introduction to the design and performance evaluation of networks and services.
  • Modelling and topological design of communication networks.
  • Modelling of network services traffic and work load.
  • Top-down network design under service requirements and various constraints.
  • Selection of most appropriate link, network and transport layer protocols.
  • Selection of most appropriate network architecture and network devices.
  • Network optimization techniques and algorithms, network reliability.
  • Performance measures.
  • Quality of service assurance.
  • Theoretical exercises and network design projects.
More »

Secondary Major in "NETWORKS" or "TELECOMMUNICATIONS": Optional Courses

DS-000 Compulsory Course of the Secondary Major that has not been chosen as compulsory course of Secondary Major [OPT/SM] -

DS-729 Energy and Environment Systems and Policies [OPT/GEN] I. Maniatis

DS-728 Learning Design [OPT/CIS] S. Retalis

DS-534 Algorithms for Electronic Markets [OPT/CIS] O. Telelis

Learning Outcomes

The course’s material includes the theory and practice that pertain to the design of economic mechanisms for automated trade exchanges, in modern digital platforms (auction websites, services provision and products retail websites, internet advertisement platforms). In particular, the course concerns the modern algorithmic techniques that facilitate the digital implementation of electronic markets.

Upon successful completion of the course, the students will be in position:

  • to understand the economic and algorithmic background that underlies the functionality of electronic markets.
  • to design electronic trade exchanges platforms, by choosing the appropriate economic mechanisms and the relevant algorithmic implementations.
  • to assess and evaluate the performance of economic mechanisms and their algorithmic implementations, relative to a given electronic market and its particulars.
  • to design, implement and evaluate automated pricing mechanisms.

Course Contents

  • Introduction to Game Theory: Strategies, Utility Functions
  • Strategic Games and Nash Equilibrium
  • Efficiency of Equilibria
  • Oligopoly Models
  • Auctions: First-Price, Second-Price, Multi-Unit Formats
  • Algorithmic Mechanism Design
  •  Sponsored Search Auctions
  • Combinatorial Auctions
  • Principles and Methods of Pricing
  • Prediction Techniques
  • Online Auctions
More »

DS-533 Data Processing Techniques [Opt/SDS] C. Doulkeridis

Learning Outcomes

The objective of this course is to familiarize students with: (a) learning access methods for large data volumes for various data formats, as well as scalable writing, (b) efficient data storage and retrieval with appropriate indexing techniques, (c) the design and implementation of data processing algorithms aiming at the development of efficient applications that manage data.

Upon successful completion of the course, the students will be in position:

  • to develop data-centric applications with emphasis in efficiency and scalability
  • to use the most appropriate indexing methods for a given problem
  • to evaluate and improve the parts of data processing algorithms that incur high computational load
  • to apply the most suitable data processing techniques that match with data under analysis and for a given query workload
  • to develop efficient data processing algorithms

Course Contents

  • Operation of disk and main memory, serial and random access, cost and efficiency, data locality on disk and main-memory, direct and indirect access, main-memory data structures (arrays, priority queues, hashing)
  • Data access techniques for structured, semi-structured and unstructured data: relational DBs, XML, RDF, text documents, web pages, web APIs, social networks.
  • One-dimensional data and indexing, B-tree, variations (B+tree, B*tree), range queries, inverted indexes.
  • Spatial data, spatial data types, spatial queries, approximation in representation, distance measures, extensions for multidimensional data.
  • Spatial indexing techniques, grid file, spatial indexes (R-tree, QuadTree), space-filling curves (Hilbert, Z-order)
  • Similarity search, k-nearest neighbor search, branch-and-bound algorithms, locality sensitive hashing (LSH), approximate k-nearest neighbor.
  • Top-k search: algorithms based on pre-processing, online algorithms, Fagin’s algorithm, index-based algorithms.
  • Join queries, spatial joins, top-k joins.
  • Spatio-textual data, query types, indexing methods, processing algorithms.
More »

DS-532 Advanced topics in data analytics [Opt/SDS] M. Halkidi

Learning Outcomes

The students after the successful completion of the course will be able:

  • to model and analyze data with appropriate analysis techniques, assess the quality of input
  • to choose the appropriate exploratory and/or inferential method for analyzing data, and interpret the results contextually.
  • to use supervised and unsupervised learning techniques for solving many analysis problems such as prediction, classification, segmentation.
  • to apply methods for the evaluation of the data analysis results.

Course Contents

  • Collection, preparation and representation of data for analysis
  • Linear, logistic regression
  • Classification Techniques (probabilistic classification, decision trees, support vector machines)
  • Predictive analytics and neural networks
  • Recommender systems
  • Graph analysis (applications on social networks)
  • Text mining – sentiment analysis
  • Evaluation of data analysis results
More »

DS-923 Information Systems Management [Opt/SDS] F. Malamateniou , E.L. Makri

Learning Outcomes

The main objective of the course is to introduce the fundamental concepts of digital systems project management and to study best practices in the area of project management such as the Project Management Body of Knowledge (PMBOK) of Project Management Institute (PMI), and to use such practices in project management of digital systems. The course will incorporate a laboratory session with project management software tools that allow students to practice some of the principles addressed.

Upon successful completion of the course the students will be able:

  • to recognize the need for IT project management
  • to recognize the key issues during the IT project management procedures
  • to describe the best practices in IT project management processes and follow an IT project management methodology –from project inception to project closure
  • to create work break down structures (WBS)
  • to create project plans
  • to create business cases
  • to describe PMI project management process groups
  • to use various methods and techniques for schedule and budget estimation
  • to use various methods and techniques for project monitoring
  • to use various methods and techniques for resource loading and leveling
  • to assign tasks and resources using project management software tools
  • to create a Gantt/PERT schedule using project management software tools
  • to monitor project progress using project management software tools

Course Contents

  • Introduction to project management (e.g. project definition, projects typology, triple constraint concept, a systems approach to project management, organizational influences).
  • Projects, information systems and services life cycles. IT project management methodologies (e.g. phases, deliverables, PMI project management procedures).
  • IT projects business cases (e.g. Measurable Organizational Value, feasibility study, risk analysis, cost-benefit analysis, financial and scoring models).
  • IT project management portfolios (e.g. project selection using Balanced Scorecard).
  • Project charters and project plans. PMI project management processes (PMBOK areas).
  • Project Time and Recourse Management (e.g. Work Breakdown Structure, Project organization structure and responsibilities, Gantt charts, the critical path, network diagramming, PDM networks, CPM/PERT, Scheduling with resource constraints).
  • Project estimation (e.g. Delphi technique, Time boxing). Software engineering metrics and approaches (e.g. Lines of Codes, Function point analysis, COCOMO).
  • Project control. Cost control (e.g. variance analysis, earned value). Performance analysis (e.g. Performances indices SPI and CPI). Forecasting (e.g. Forecasted cost to complete project, forecasted cost at completion).
More »

DS-513 Network Oriented Information Systems [CSM/IS] A. Niros

Learning Outcomes

The aim of this course is to explain the nature and basic characteristics of the Information Systems that are run and managed over a network. With the completion of the course, the student will be in position:

  • to understand and become familiar with the key aspect for the design and development of network-oriented information systems.
  • to know the main characteristics of the information systems, the required interfaces and the approaches to realize the network-oriented aspect of such information systems.
  • to be able to implement network-oriented information systems, by utilizing programming techniques and methods.

Course Contents

  • Information Systems and Networks.
  • Portals, Middleware, Integration, Enterprise Application Integration, Enterprise Service Bus.
  • Web Services, Service-Oriented Architectures, SOA governance.
  • Organizational change, the impact of integrated network oriented IS on organizations.
  • Enterprise Resource Planning applications, Customer Relationship Management systems, Supply Chain Management solutions, e-business applications.

Moreover, the EVDOXOS system is utilized to provide additional useful information to the students as well as exercises that respond to the corresponding thematic topics / sessions covered by the course.

More »

DS-703 e-Learning Systems [OPT/CIS] D. Sampson

Learning Outcomes

Upon successful completion of the course the students will be able:

  • to know and understand the key concepts of digital teaching and learning
  • to analyse, assess, select and justify pedagogically appropriate e-learning methods and tools for digital teaching and learning innovations.
  • to design and create pedagogically grounded online courses.

Course Contents

  • Online Teaching and Learning: Theoretical Underpinnings
  • Educational Design for Online Teaching and Learning
  • An hierarchical Open Access to Online Education framework: Elements (Open Educational Resources, Learning Activities and Lesson Plans, Online Courses, Digital Learning Spaces). Tools and Key Roles (Online Education Instructional Designers, e-Tutors, e-Learning Systems Administrators, Managers)
  • Open Educational Resources: Learning Objects, Educational Metadata, Repositories of Learning Objects. Case Studies: the National Repositories of Learning Objects
  • Learning Activities and Lesson Plans: Authoring Tools for Learning Activities and Lesson Plans, Repositories of Learning Activities and Lesson Plans. Case Studies: the National Repositories of Learning Activities and Lesson Plans
  • Design, Development and Delivery of Online Courses: Methodology for Designing Online Courses. Authoring Tools for Developing Online Courses. Course Management Systems. Case Study: Open edX, MOODLE
  • Digital Learning Spaces: 3D Virtual Classrooms and Laboratories
More »

DS-514 e-Business [Opt/SDS] A. Niros

Learning Outcomes

This course presents baselines on digital economy. With the completion of the course, the student will be in position:

  • to understand and become familiar with the key concepts and principles of applications of e-business.
  • to know the main characteristics of the e-business applications both in terms of development and in terms of provisioning of such applications.
  • to be able to implement e-business applications, by applying the knowledge obtained from laboratory exercises in different application contexts / domains.

Course Contents

  • e-Business introduction.
  • e-Commerce presentation.
  • Baselines on e-business micro-economy theory.
  • Business requirements analysis for the design of e-commerce.
  • Methodology for the design of successful web pages. Blogs.
  • e-Stores, methodology for the design of e-stores.
  • Design evaluation and faults detection through the use of web statistics applications.
  • eGovernment, ebanking; ehealth; business-to-business applications.

Moreover, the EVDOXOS system is utilized to provide additional useful information to the students as well as exercises that respond to the corresponding thematic topics / sessions covered by the course.

More »

DS-806 Cryptography [OPT/SEC] C. Xenakis , E.L. Makri

Learning Outcomes

The aim of this course is to support the students in learning the principles, concepts and applications of cryptography.
Upon successful completion of the course the student will be able:

  • to handle the basic elements of numerical theory and modular arithmetic
  • to manage cryptographic algorithms and their properties
  • basic cryptographic functions, such as pseudo-random sequences, one-way hash functions, shift and displacement networks and feistel networks.
  • the main features for symmetric and asymmetric cryptography are familiar
  • to handle key management systems and digital signatures

Course Contents

  • Basic definitions and concepts; information security.
  • Symmetric cryptography.
  • Digital signatures.
  • Authentication.
  • Public key cryptography.
  • Hash functions.
  • Integrity checking.
  • Key management and random number generators.
More »

DS-310 Wireless Sensor Networks [Opt/T&N] A. Alexiou

Learning Outcomes

The objective of this course is to focus on short range communications with emphasis on wireless local area networks (WiFi), adhoc networks, wireless sensor networks and applications.

At the end of this course, students will have acquired advanced/in depth knowledge in the field of Short Range Communications, with particular emphasis on baseband processing physical layer techniques, and Medium Access Control design.

The students will be capable of performing numerical calculations of various wireless parameters, stochastic modelling of wireless transceivers and performance assessment by means of analytical evaluations and simulations. The students will also be capable of comprehending the design principle of Wireless Local Area Networks and Wireless Sensor Networks of Internet of Things applications.

Course Contents

  • WiFi techniques, technologies, protocols and standards.
  • Short range communications: Personal Area Networks (PAN), Body Area Networks (BAN), Ultra Wide Band communications.
  • AdHoc Networks: Physical layer and transceiver design, MAC layer design, connectivity, topologies and routing.
  • Wireless Sensor Networks: Information-theoretic bounds on sensor network performance, detection and estimation, cooperative transmission, localization and positioning, energy efficiency.
  • Applications: eCommerce, safety, digital home, eHealth.
More »

DS-520 Ιntelligent Agents and Multiagent Systems [CSM/CAS] G. Vouros

Learning Outcomes

Upon successful completion of this course, students should be able to know principles, paradigmatic architectures and methods for developing single agent and multi agent systems, have a critical and informed view of strengths and limitations regarding agents and multi agent systems, towards designing and delivering such systems.

Specifically, students know and acquire the abilities to develop:

  • Architectures of single and multi-agent systems
  • Methods for agents coordination, collaboration and competition in specific settings and paradigmatic environments and problems
  • Agents’ communication methods and protocols

Via the critical view of agents technology and experience in developing such systems.

Course Contents

  • Agents: Principles, architectures and application examples
  • Deliberation vs Reaction: Architectures
  • Mental attitudes, states and their representation
  • Multi-agent Systems: Interactions and dependencies
  • Multiagent organizations and communication
  • Cooperation and collaboration
  • Agents communication
More »

DS-920 Student Placement [OPT/GEN] -

The students can choose it only once during undergraduate studies (either the 7th or the 8th semester).

More »

DS-313 Development of Telecommunication Systems [Opt/T&N] D. Georgiou

Learning Outcomes

The aim of this course is to familiarize students with best practices for the design and implementation of modern innovative telecom systems and applications. The main topics discussed include systematic multi-criteria requirement analysis, transformation of user requirements to architectural specifications and system functionality, design optimization for high performance and QoS, installation and deployment procedures, as well as system validation against initial requirements and specifications. The presented methodologies derive analytically from real case studies of innovative telecommunication systems and applications with extremely high added value and impact (e.g. the European Space Agency SATWAYS project in the field of Air Traffic Control). Students will further gain significant practical experience in the design and implementation of innovative telecommunication systems through exercise solving and development of small projects. Last but not least, the course presents an in-depth commercial feasibility analysis of the developed systems.

At the end of the course, students will be equipped with advanced expert and analytical knowledge for the consistent design, development and validation of innovative embedded telecommunication systems (see Course Content) meeting strict quality requirements regarding the provided telecommunication services. The obtained knowledge will allow the critical and analytical deepening as well as performing innovative research in the broad scientific domain of embedded telecommunication systems and applications.

Students will be capable of:

  • transforming user requirements to telecommunication systems architectural specifications and functionality.
  • specifying prototype embedded telecommunication systems, including their architectural layering (hardware, embedded software, software), according to specific QoS requirements for the provided services.
  • designing and specifying modern voice communication systems for next generation networks.
  • designing QoS models involving the end-to-end telecommunication transmission path from service provisioning to the end user, as well as extracting performance requirements and specifications for segments of the end-to-end transmission path.
  • optimizing the design of telecommunication systems for high performance and QoS.
  • explaining the details of the E-model adaptation and simplification of the discrete noise and advantage parameters in the demanding field of radio voice communications. The E-model (ITU-T Rec. G.107) is a transmission planning tool that provides a prediction of the expected voice quality, as perceived by a typical telephone user, for a complete end-to-end (i.e. mouth-to-ear) telephone connection under conversational conditions.
  • exploiting and solving the adapted voice QoS model for extracting system performance design parameters (e.g. for selecting appropriate voice codecs assuming a limited end-to-end delay and the constant values of delay parameters along the telecommunication transmission path segments).
  • compiling detailed plans for technical validation of system deliverables against the initial user requirements and system specifications.
  • analyzing the satellite link budget for the provisioning of telecommunication services and extracting requirements regarding the underlying telecommunication system.
  • analyzing the installation, deployment and operational details of the developed systems.
  • compiling workplans, work packages, time schedules, lists of technical deliverables and reports, critical paths, milestones and sample budgets involving R&D projects that design and develop innovative embedded telecommunication systems.
  • performing indicative techno-economic studies and commercial feasibility analysis regarding innovative embedded telecommunication systems, including a SWOT analysis (strengths, weaknesses, opportunities, threats).

Course Contents

  • Exemplary Innovative telecommunication systems and applications with high added value and impact.
  • Systematic multi-criteria requirement analysis.
  • Transformation of user requirements to architectural specifications and system functionality.
  • Design optimization for high performance and QoS.
  • Adaptation and validation of the E-model in the radio communications use case, including satellite transmission. The E-model (ITU-T Rec. G.107) is a transmission planning tool that provides a prediction of the expected voice quality, as perceived by a typical telephone user, for a complete end-to-end (i.e. mouth-to-ear) telephone connection under conversational conditions.
  • Exploitation of the voice QoS model for extracting system performance design parameters (e.g. for selecting appropriate voice codecs assuming a limited end-to-end delay and the constant values of delay parameters along the telecommunication transmission path segments).
  • Voice communications based on the NGN (Next Generation Network) standard.
  • Installation procedures and relevant issues.
  • System validation against initial requirements and specifications.
  • Commercial feasibility analysis.
  • Exercises and programming projects.
More »

DS-208 Ιnteroperability Systems [Opt/SDS] A. Prentza , E. Stougiannou

Learning Outcomes

The aim of this course is the familiarization of the students with the concept of systems interoperability, the understanding of basic concepts and the acquirement of essential knowledge in systems interoperability providing them with the ability to analyze and improve skills that will help them both in the scientific and professional field. The course introduces the students to fundamental principles of systems interoperability.

Course Contents

  • Introduction to systems interoperability
  • Basic principles, definitions and benefits
  • Main approaches and requirements
  • International Standards and Initiatives
  • European Interoperability Framework
  • Interoperability at organizational, semantic and technical level
  • Methodology for designing interoperable digital services
  • Interoperable public services
  • Interoperability in eProcurement
  • Interoperability in eInvoicing
  • Interoperability in eHealth
More »

DS-903 Human Factor Management [OPT/GEN] Faculty of the Department of BA, K. Poupouza

  • Course Code DS-903 Type of Course Opt./General
  • Theory/Lab Sessions 4 hours / 2 hours ECTS Credits 5
  • Semester 7th Semester FacultyFaculty of the Department of BA, K. Poupouza

This course offered by Department of Business Administration of University of Piraeus.

More »

DS-910 Business Policy and Strategic [OPT/GEN] Faculty of the Department of BA, K. Poupouza

  • Course Code DS-910 Type of Course Opt./General
  • Theory/Lab Sessions 4 hours / 2 hours ECTS Credits 5
  • Semester 7th Semester FacultyFaculty of the Department of BA, K. Poupouza

This course offered by the Department of Business Administration of University of Piraeus.

More »

DS-404 Pattern Recognition [CSM/DM] I. Maglogiannis , K. Moutselos

Learning Outcomes

Pattern recognition is the scientific field that deals with the assignment of a label to a given input value. An example of pattern recognition is classification, which attempts to assign each input value to one of a given set of classes. The course aims to cover the most popular in the literature techniques for pattern recognition, as they are typically employed in a number of practical applications, such as speech and audio recognition, image and video analysis, biometrics and bioinformatics. The course covers the most commonly used classification algorithms, feature selection techniques, data transformation methods, and data clustering.

Course Contents

  • Introduction to Pattern recognition systems
  • Parametric estimation of probability density function (maximum Likelihood estimation, maximum a posteriori
  • Bayesian classifiers and Bayesian Networks
  • k-nearest neighbor
  • Non parametric estimation of probability density function (Parzen windows)
  • Linear classifiers, non linear classifiers. Perceptron algorithm. Multilayer neural networks
  • Unsupervised Pattern recognition – Clustering
  • Feature generation: contour representation and contour tracing, chain code, polygon, signatures, linear transforms, Fourier Transform, regional features, image recognition, bias and variance, texture
  • Feature Selection and Kernels
  • Pattern recognition tools
More »

DS-701 Educational Digital Systems [CSM/DS] D. Sampson

Learning Outcomes

With the completion of the course, the student will be able:

  • to know and understand the key concepts of exploiting digital technologies in teaching, learning and assessment of learning in K12 School Education.
  • to analyse, assess, select and justify a pedagogically appropriate educational technologies to support different teaching strategies in K12 School Education.
  • to design and create pedagogically grounded technology-supported teaching and learning scenarios for the K12 education.

The learning objectives of the course are aligned to the Greek State qualification framework for a teaching licence in K12 school education.

Course Contents

  • 1. Technology-Supported and Technology-Enhanced Teaching and Learning in School Education: Theoretical Underpinnings
  • 2. Integrating Technology in School Education (teaching, learning and assessment of learning): Models and Practice
  • 3. Taxonomy of Educational Technologies in School Education
  • 4. Educational Technologies for supporting different teaching and learning strategies
    • 4.1. Tutorials
    • 4.2. Drill and Practice
    • 4.3. Problem solving
    • 4.4. Modeling
    • 4.5. Virtual Labs and Simulations
    • 4.6. Inquiry-based Learning
    • 4.7. Collaborative Learning
    • 4.8. Assessment of Learning
    • o 4.9. Educational Games
  • 5. Digital School Infrastructure
    • 5.1. Interactive Boards
    • 5.2. ICT School Laboratory
More »

DS-706 Instructional Methods [OPT/GEN] F. Paraskeva, S. Retalis

Learning Outcomes

This course is designed to promote a fundamental understanding of the theoretical and applied knowledge related to instructional theories and models (principles, methods, strategies) for the design, development, implementation and evaluation of Technology Enhanced Learning Environments (TELE).

At completion of the course, the students will be able:

  • to describe the fundamental principles of instructional theories and models
  • to identify learners’ personal characteristics (learning styles, needs, motivations, attitudes) and how to apply them into educational practice (emphasizing on the processes by which individuals learn).
  • to apply these principles to learner – centered teaching.
  • to examine, analyze, design, develop and evaluate different types of instructional methods & strategies (discussions, lecturing, delivery media, support tools, collaborative learning, cases/simulations, etc.), for an effective teaching.
  • to demonstrate a knowledge of the ‘what’, ‘how’, and ‘when’, in the instructional design process in different disciplines.
  • to show mastery of various teaching methodologies.
  • to integrate ICT educational technologies into activities for K-16 and business settings.
  • to choose the appropriate institutional resources for the course/student development.
  • to show knowledge of the theory (Bloom’s Taxonomy etc) by designing lessons that utilize all levels of higher level intellectual/cognitive/metacognitive skills.
  • to implement teaching and presentation skills into educational and business setting.
  • to articulate strategies for addressing the needs of culturally diverse and special needs students. (
  • to create an educational plan/scenario for reflective thinking into educational practice.
  • to create the appropriate orchestrated instructional methods and strategies for an effective teaching.
  • to construct an integrated unit of instruction.
  • to provide the assignments (readings, case studies), individually and collaboratively (team effort).
  • to collaborate with classmates in designing instructional projects.
  • to show their ability to work with students one-on-one, in small groups, and in large groups through lab settings.
  • to articulate a personal set of values and a vision for their future classroom.

Course Contents

  • Introduction to the subject: Education – Learning – Instruction – Training.
  • the basic principles of the processing of learning (behavioral and cognitive approach, the cognitive and social constructivist theories in specific instructional methods).
  • the factors that influence instructional and learning outcomes (individual differences, self-efficacy beliefs, motivations, needs, attitudes, locus of control).
  • the personal and psychological factors in learning and instruction (learning styles, cognitive learning styles) and the implication on TELE (AHLE, smart education, e-portfolios, educational games, gamification).
  • the models of teaching and instructional design: Gagne’s Nine Events of Instruction, Piaget, Bruner, PBL, SRL, ADDIE Kirkpatrick model, MPI).
  • the taxonomies and learning objectives: design patterns/frameworks, methods, learning strategies, techniques, activities, evaluation (Bloom’s Taxonomy).
  • the formative, summative and authentic assessment.
  • the ICT in educational settings (synchronous and asynchronous learning, blended learning, flipped classroom, STEAM).
  • the ICT applications on instructional methodologies in educational and training settings (lesson plans, educational scenarios).
  • the applications using ICT in education (web 2.0 environments: wikis & blogs, LMS, web-based tools, authoring tools etc).
  • the school and professional environment, (interpersonal relationships, communication, ethics, etc).
  • socio-cultural politics of instruction (integrating different cultures).
More »

DS-330 Systems Simulation [Opt/T&N] A. Rouskas

Learning Outcomes

The course presents simulation techniques with particular emphasis on simulation of computer computational systems and communication networks. At the end of the course the students will be able to design models and develop simulation programs for the study and performance evaluation of complex computational systems and network communication.

Course Contents

  • Introduction to dynamic discrete event systems.
  • Development of discrete system models, event-advance design, time-advance design, activity-based design.
  • Pseudorandom number generation, random variables generation.
  • Overview of simulation languages and platforms.
  • Development of simulation programs using general purpose programming languages.
  • Measurement techniques, traffic load and experiment design.
  • Statistical analysis of simulation experiments, transient and steady state, data collection, confidence intervals, variation reduction techniques.
  • Simulation exercises and examples of data networks and cloud computing systems. Theoretical results verification.
More »

MAJOR IN "SOFTWARE & DATA SYSTEMS"

Secondary Major in "INFORMATION SYSTEMS": Compulsory Courses

DS-513 Network Oriented Information Systems [CSM/IS] A. Niros

Learning Outcomes

The aim of this course is to explain the nature and basic characteristics of the Information Systems that are run and managed over a network. With the completion of the course, the student will be in position:

  • to understand and become familiar with the key aspect for the design and development of network-oriented information systems.
  • to know the main characteristics of the information systems, the required interfaces and the approaches to realize the network-oriented aspect of such information systems.
  • to be able to implement network-oriented information systems, by utilizing programming techniques and methods.

Course Contents

  • Information Systems and Networks.
  • Portals, Middleware, Integration, Enterprise Application Integration, Enterprise Service Bus.
  • Web Services, Service-Oriented Architectures, SOA governance.
  • Organizational change, the impact of integrated network oriented IS on organizations.
  • Enterprise Resource Planning applications, Customer Relationship Management systems, Supply Chain Management solutions, e-business applications.

Moreover, the EVDOXOS system is utilized to provide additional useful information to the students as well as exercises that respond to the corresponding thematic topics / sessions covered by the course.

More »

Secondary Major in "DATA MANAGEMENT": Compulsory Courses

DS-404 Pattern Recognition [CSM/DM] I. Maglogiannis , K. Moutselos

Learning Outcomes

Pattern recognition is the scientific field that deals with the assignment of a label to a given input value. An example of pattern recognition is classification, which attempts to assign each input value to one of a given set of classes. The course aims to cover the most popular in the literature techniques for pattern recognition, as they are typically employed in a number of practical applications, such as speech and audio recognition, image and video analysis, biometrics and bioinformatics. The course covers the most commonly used classification algorithms, feature selection techniques, data transformation methods, and data clustering.

Course Contents

  • Introduction to Pattern recognition systems
  • Parametric estimation of probability density function (maximum Likelihood estimation, maximum a posteriori
  • Bayesian classifiers and Bayesian Networks
  • k-nearest neighbor
  • Non parametric estimation of probability density function (Parzen windows)
  • Linear classifiers, non linear classifiers. Perceptron algorithm. Multilayer neural networks
  • Unsupervised Pattern recognition – Clustering
  • Feature generation: contour representation and contour tracing, chain code, polygon, signatures, linear transforms, Fourier Transform, regional features, image recognition, bias and variance, texture
  • Feature Selection and Kernels
  • Pattern recognition tools
More »

Secondary Major in "INFORMATION SYSTEMS" or "DATA MANAGEMENT": Optional Courses

DS-000 Compulsory Course of the Secondary Major that has not been chosen as compulsory course of Secondary Major [OPT/SM] -

DS-729 Energy and Environment Systems and Policies [OPT/GEN] I. Maniatis

DS-728 Learning Design [OPT/CIS] S. Retalis

DS-534 Algorithms for Electronic Markets [OPT/CIS] O. Telelis

Learning Outcomes

The course’s material includes the theory and practice that pertain to the design of economic mechanisms for automated trade exchanges, in modern digital platforms (auction websites, services provision and products retail websites, internet advertisement platforms). In particular, the course concerns the modern algorithmic techniques that facilitate the digital implementation of electronic markets.

Upon successful completion of the course, the students will be in position:

  • to understand the economic and algorithmic background that underlies the functionality of electronic markets.
  • to design electronic trade exchanges platforms, by choosing the appropriate economic mechanisms and the relevant algorithmic implementations.
  • to assess and evaluate the performance of economic mechanisms and their algorithmic implementations, relative to a given electronic market and its particulars.
  • to design, implement and evaluate automated pricing mechanisms.

Course Contents

  • Introduction to Game Theory: Strategies, Utility Functions
  • Strategic Games and Nash Equilibrium
  • Efficiency of Equilibria
  • Oligopoly Models
  • Auctions: First-Price, Second-Price, Multi-Unit Formats
  • Algorithmic Mechanism Design
  •  Sponsored Search Auctions
  • Combinatorial Auctions
  • Principles and Methods of Pricing
  • Prediction Techniques
  • Online Auctions
More »

DS-533 Data Processing Techniques [Opt/SDS] C. Doulkeridis

Learning Outcomes

The objective of this course is to familiarize students with: (a) learning access methods for large data volumes for various data formats, as well as scalable writing, (b) efficient data storage and retrieval with appropriate indexing techniques, (c) the design and implementation of data processing algorithms aiming at the development of efficient applications that manage data.

Upon successful completion of the course, the students will be in position:

  • to develop data-centric applications with emphasis in efficiency and scalability
  • to use the most appropriate indexing methods for a given problem
  • to evaluate and improve the parts of data processing algorithms that incur high computational load
  • to apply the most suitable data processing techniques that match with data under analysis and for a given query workload
  • to develop efficient data processing algorithms

Course Contents

  • Operation of disk and main memory, serial and random access, cost and efficiency, data locality on disk and main-memory, direct and indirect access, main-memory data structures (arrays, priority queues, hashing)
  • Data access techniques for structured, semi-structured and unstructured data: relational DBs, XML, RDF, text documents, web pages, web APIs, social networks.
  • One-dimensional data and indexing, B-tree, variations (B+tree, B*tree), range queries, inverted indexes.
  • Spatial data, spatial data types, spatial queries, approximation in representation, distance measures, extensions for multidimensional data.
  • Spatial indexing techniques, grid file, spatial indexes (R-tree, QuadTree), space-filling curves (Hilbert, Z-order)
  • Similarity search, k-nearest neighbor search, branch-and-bound algorithms, locality sensitive hashing (LSH), approximate k-nearest neighbor.
  • Top-k search: algorithms based on pre-processing, online algorithms, Fagin’s algorithm, index-based algorithms.
  • Join queries, spatial joins, top-k joins.
  • Spatio-textual data, query types, indexing methods, processing algorithms.
More »

DS-532 Advanced topics in data analytics [Opt/SDS] M. Halkidi

Learning Outcomes

The students after the successful completion of the course will be able:

  • to model and analyze data with appropriate analysis techniques, assess the quality of input
  • to choose the appropriate exploratory and/or inferential method for analyzing data, and interpret the results contextually.
  • to use supervised and unsupervised learning techniques for solving many analysis problems such as prediction, classification, segmentation.
  • to apply methods for the evaluation of the data analysis results.

Course Contents

  • Collection, preparation and representation of data for analysis
  • Linear, logistic regression
  • Classification Techniques (probabilistic classification, decision trees, support vector machines)
  • Predictive analytics and neural networks
  • Recommender systems
  • Graph analysis (applications on social networks)
  • Text mining – sentiment analysis
  • Evaluation of data analysis results
More »

DS-923 Information Systems Management [Opt/SDS] F. Malamateniou , E.L. Makri

Learning Outcomes

The main objective of the course is to introduce the fundamental concepts of digital systems project management and to study best practices in the area of project management such as the Project Management Body of Knowledge (PMBOK) of Project Management Institute (PMI), and to use such practices in project management of digital systems. The course will incorporate a laboratory session with project management software tools that allow students to practice some of the principles addressed.

Upon successful completion of the course the students will be able:

  • to recognize the need for IT project management
  • to recognize the key issues during the IT project management procedures
  • to describe the best practices in IT project management processes and follow an IT project management methodology –from project inception to project closure
  • to create work break down structures (WBS)
  • to create project plans
  • to create business cases
  • to describe PMI project management process groups
  • to use various methods and techniques for schedule and budget estimation
  • to use various methods and techniques for project monitoring
  • to use various methods and techniques for resource loading and leveling
  • to assign tasks and resources using project management software tools
  • to create a Gantt/PERT schedule using project management software tools
  • to monitor project progress using project management software tools

Course Contents

  • Introduction to project management (e.g. project definition, projects typology, triple constraint concept, a systems approach to project management, organizational influences).
  • Projects, information systems and services life cycles. IT project management methodologies (e.g. phases, deliverables, PMI project management procedures).
  • IT projects business cases (e.g. Measurable Organizational Value, feasibility study, risk analysis, cost-benefit analysis, financial and scoring models).
  • IT project management portfolios (e.g. project selection using Balanced Scorecard).
  • Project charters and project plans. PMI project management processes (PMBOK areas).
  • Project Time and Recourse Management (e.g. Work Breakdown Structure, Project organization structure and responsibilities, Gantt charts, the critical path, network diagramming, PDM networks, CPM/PERT, Scheduling with resource constraints).
  • Project estimation (e.g. Delphi technique, Time boxing). Software engineering metrics and approaches (e.g. Lines of Codes, Function point analysis, COCOMO).
  • Project control. Cost control (e.g. variance analysis, earned value). Performance analysis (e.g. Performances indices SPI and CPI). Forecasting (e.g. Forecasted cost to complete project, forecasted cost at completion).
More »

DS-703 e-Learning Systems [OPT/CIS] D. Sampson

Learning Outcomes

Upon successful completion of the course the students will be able:

  • to know and understand the key concepts of digital teaching and learning
  • to analyse, assess, select and justify pedagogically appropriate e-learning methods and tools for digital teaching and learning innovations.
  • to design and create pedagogically grounded online courses.

Course Contents

  • Online Teaching and Learning: Theoretical Underpinnings
  • Educational Design for Online Teaching and Learning
  • An hierarchical Open Access to Online Education framework: Elements (Open Educational Resources, Learning Activities and Lesson Plans, Online Courses, Digital Learning Spaces). Tools and Key Roles (Online Education Instructional Designers, e-Tutors, e-Learning Systems Administrators, Managers)
  • Open Educational Resources: Learning Objects, Educational Metadata, Repositories of Learning Objects. Case Studies: the National Repositories of Learning Objects
  • Learning Activities and Lesson Plans: Authoring Tools for Learning Activities and Lesson Plans, Repositories of Learning Activities and Lesson Plans. Case Studies: the National Repositories of Learning Activities and Lesson Plans
  • Design, Development and Delivery of Online Courses: Methodology for Designing Online Courses. Authoring Tools for Developing Online Courses. Course Management Systems. Case Study: Open edX, MOODLE
  • Digital Learning Spaces: 3D Virtual Classrooms and Laboratories
More »

DS-514 e-Business [Opt/SDS] A. Niros

Learning Outcomes

This course presents baselines on digital economy. With the completion of the course, the student will be in position:

  • to understand and become familiar with the key concepts and principles of applications of e-business.
  • to know the main characteristics of the e-business applications both in terms of development and in terms of provisioning of such applications.
  • to be able to implement e-business applications, by applying the knowledge obtained from laboratory exercises in different application contexts / domains.

Course Contents

  • e-Business introduction.
  • e-Commerce presentation.
  • Baselines on e-business micro-economy theory.
  • Business requirements analysis for the design of e-commerce.
  • Methodology for the design of successful web pages. Blogs.
  • e-Stores, methodology for the design of e-stores.
  • Design evaluation and faults detection through the use of web statistics applications.
  • eGovernment, ebanking; ehealth; business-to-business applications.

Moreover, the EVDOXOS system is utilized to provide additional useful information to the students as well as exercises that respond to the corresponding thematic topics / sessions covered by the course.

More »

DS-806 Cryptography [OPT/SEC] C. Xenakis , E.L. Makri

Learning Outcomes

The aim of this course is to support the students in learning the principles, concepts and applications of cryptography.
Upon successful completion of the course the student will be able:

  • to handle the basic elements of numerical theory and modular arithmetic
  • to manage cryptographic algorithms and their properties
  • basic cryptographic functions, such as pseudo-random sequences, one-way hash functions, shift and displacement networks and feistel networks.
  • the main features for symmetric and asymmetric cryptography are familiar
  • to handle key management systems and digital signatures

Course Contents

  • Basic definitions and concepts; information security.
  • Symmetric cryptography.
  • Digital signatures.
  • Authentication.
  • Public key cryptography.
  • Hash functions.
  • Integrity checking.
  • Key management and random number generators.
More »

DS-310 Wireless Sensor Networks [Opt/T&N] A. Alexiou

Learning Outcomes

The objective of this course is to focus on short range communications with emphasis on wireless local area networks (WiFi), adhoc networks, wireless sensor networks and applications.

At the end of this course, students will have acquired advanced/in depth knowledge in the field of Short Range Communications, with particular emphasis on baseband processing physical layer techniques, and Medium Access Control design.

The students will be capable of performing numerical calculations of various wireless parameters, stochastic modelling of wireless transceivers and performance assessment by means of analytical evaluations and simulations. The students will also be capable of comprehending the design principle of Wireless Local Area Networks and Wireless Sensor Networks of Internet of Things applications.

Course Contents

  • WiFi techniques, technologies, protocols and standards.
  • Short range communications: Personal Area Networks (PAN), Body Area Networks (BAN), Ultra Wide Band communications.
  • AdHoc Networks: Physical layer and transceiver design, MAC layer design, connectivity, topologies and routing.
  • Wireless Sensor Networks: Information-theoretic bounds on sensor network performance, detection and estimation, cooperative transmission, localization and positioning, energy efficiency.
  • Applications: eCommerce, safety, digital home, eHealth.
More »

DS-520 Ιntelligent Agents and Multiagent Systems [CSM/CAS] G. Vouros

Learning Outcomes

Upon successful completion of this course, students should be able to know principles, paradigmatic architectures and methods for developing single agent and multi agent systems, have a critical and informed view of strengths and limitations regarding agents and multi agent systems, towards designing and delivering such systems.

Specifically, students know and acquire the abilities to develop:

  • Architectures of single and multi-agent systems
  • Methods for agents coordination, collaboration and competition in specific settings and paradigmatic environments and problems
  • Agents’ communication methods and protocols

Via the critical view of agents technology and experience in developing such systems.

Course Contents

  • Agents: Principles, architectures and application examples
  • Deliberation vs Reaction: Architectures
  • Mental attitudes, states and their representation
  • Multi-agent Systems: Interactions and dependencies
  • Multiagent organizations and communication
  • Cooperation and collaboration
  • Agents communication
More »

DS-920 Student Placement [OPT/GEN] -

The students can choose it only once during undergraduate studies (either the 7th or the 8th semester).

More »

DS-313 Development of Telecommunication Systems [Opt/T&N] D. Georgiou

Learning Outcomes

The aim of this course is to familiarize students with best practices for the design and implementation of modern innovative telecom systems and applications. The main topics discussed include systematic multi-criteria requirement analysis, transformation of user requirements to architectural specifications and system functionality, design optimization for high performance and QoS, installation and deployment procedures, as well as system validation against initial requirements and specifications. The presented methodologies derive analytically from real case studies of innovative telecommunication systems and applications with extremely high added value and impact (e.g. the European Space Agency SATWAYS project in the field of Air Traffic Control). Students will further gain significant practical experience in the design and implementation of innovative telecommunication systems through exercise solving and development of small projects. Last but not least, the course presents an in-depth commercial feasibility analysis of the developed systems.

At the end of the course, students will be equipped with advanced expert and analytical knowledge for the consistent design, development and validation of innovative embedded telecommunication systems (see Course Content) meeting strict quality requirements regarding the provided telecommunication services. The obtained knowledge will allow the critical and analytical deepening as well as performing innovative research in the broad scientific domain of embedded telecommunication systems and applications.

Students will be capable of:

  • transforming user requirements to telecommunication systems architectural specifications and functionality.
  • specifying prototype embedded telecommunication systems, including their architectural layering (hardware, embedded software, software), according to specific QoS requirements for the provided services.
  • designing and specifying modern voice communication systems for next generation networks.
  • designing QoS models involving the end-to-end telecommunication transmission path from service provisioning to the end user, as well as extracting performance requirements and specifications for segments of the end-to-end transmission path.
  • optimizing the design of telecommunication systems for high performance and QoS.
  • explaining the details of the E-model adaptation and simplification of the discrete noise and advantage parameters in the demanding field of radio voice communications. The E-model (ITU-T Rec. G.107) is a transmission planning tool that provides a prediction of the expected voice quality, as perceived by a typical telephone user, for a complete end-to-end (i.e. mouth-to-ear) telephone connection under conversational conditions.
  • exploiting and solving the adapted voice QoS model for extracting system performance design parameters (e.g. for selecting appropriate voice codecs assuming a limited end-to-end delay and the constant values of delay parameters along the telecommunication transmission path segments).
  • compiling detailed plans for technical validation of system deliverables against the initial user requirements and system specifications.
  • analyzing the satellite link budget for the provisioning of telecommunication services and extracting requirements regarding the underlying telecommunication system.
  • analyzing the installation, deployment and operational details of the developed systems.
  • compiling workplans, work packages, time schedules, lists of technical deliverables and reports, critical paths, milestones and sample budgets involving R&D projects that design and develop innovative embedded telecommunication systems.
  • performing indicative techno-economic studies and commercial feasibility analysis regarding innovative embedded telecommunication systems, including a SWOT analysis (strengths, weaknesses, opportunities, threats).

Course Contents

  • Exemplary Innovative telecommunication systems and applications with high added value and impact.
  • Systematic multi-criteria requirement analysis.
  • Transformation of user requirements to architectural specifications and system functionality.
  • Design optimization for high performance and QoS.
  • Adaptation and validation of the E-model in the radio communications use case, including satellite transmission. The E-model (ITU-T Rec. G.107) is a transmission planning tool that provides a prediction of the expected voice quality, as perceived by a typical telephone user, for a complete end-to-end (i.e. mouth-to-ear) telephone connection under conversational conditions.
  • Exploitation of the voice QoS model for extracting system performance design parameters (e.g. for selecting appropriate voice codecs assuming a limited end-to-end delay and the constant values of delay parameters along the telecommunication transmission path segments).
  • Voice communications based on the NGN (Next Generation Network) standard.
  • Installation procedures and relevant issues.
  • System validation against initial requirements and specifications.
  • Commercial feasibility analysis.
  • Exercises and programming projects.
More »

DS-303 Satellite Communications [CSM/TEL] A. Kanatas

Learning Outcomes

The course provides the basic principles of cellular mobile communication systems. It also provides the methodologies of analysis and design of these systems. By concluding the course, students are able to analyze and design basic mobile communication systems by emphasizing in physical layer techniques. Specifically, students may recognize, describe and distinguish the characteristics of several type of cells, communication channels and multiple access techniques.

Moreover, ingredient components of a cellular system are described, and students are able to analyze and design systems with different requirements of telecommunication traffic and quality links. The analysis and design are based on the identification of several criteria, on the computation of thresholds of performance of links, on the comparison of alternative implementation plans and on the evaluation of the total performance of digital systems.

The lab sessions aim to provide a deeper understanding of physical phenomena of propagation in the wireless channel and the simulation of cellular systems.

Course Contents

  • Initially, basic concepts of Mobile Communications Radiosystems are provided (cell types, communication channel types, basic cellular system operations).
  • Next, the basic Network Access Techniques (Multiple Access Techniques, Random Access Techniques) are discussed.
  • Also, reference is made to the evolution of Wireless Communication Systems (1st, 2nd, 3rd, and 4th generation cellular systems, Wireless Telephony Systems, Paging Systems, WLANs, WPANs, PMRs).
  • Students are introduced to the concept of cells and frequency reuse (elements from regular hexagon geometry, cellular systems design).
  • Then the basic concepts of telecommunication traffic analysis and systems performance is provided (elements of Queuing Theory, Erlang B model, Erlang C model, spectral performance of cellular systems).
  • In the following the main wireless propagation mechanisms are presented (multipath propagation, Doppler fading and shift, propagation loss, shadowing, coverage area definition, radio channel capacity limits).
  • Also, interference types (co-channel interference and noise, neighboring channel interference) as well as handover and performance techniques (categorization of handover techniques, advantages and disadvantages of techniques, stable performance, dynamic performance, elastic performance) are discussed and compared.
  • Then techniques for improving spectral efficiency (sectoring, cell splitting) are analyzed.
  • Finally, elements and techniques of physical layer design (modulation and coding techniques, co-channel interference mitigation techniques) are presented and a presentation of standardized Mobile Communications Systems (GSM, GPRS, 3G and 4G) is presented.
  • In addition, extra content (in evdoxos.ds.unipi.gr) like articles, audiovisual lectures and Internet addresses, as well as exercises for student’s practice are posted electronically.
  • Case studies, exemplary problems and methods for solving them are presented.
More »

DS-331 Design and Optimization of Networks [CSM/NET] A. Rouskas

Learning Outcomes

This course targets on the design, evaluation and optimization of networks and services. The course is following the approach of top-down network design, that is most commonly encountered on medium to large scale networking projects. At the end of the course the students will be able to understand and evaluate alternative design options at every stage of data networks design, including requirement and specification definition, logical and physical design, selection of appropriate technologies and protocols, implementation, testing and optimization.

Course Contents

  • Introduction to the design and performance evaluation of networks and services.
  • Modelling and topological design of communication networks.
  • Modelling of network services traffic and work load.
  • Top-down network design under service requirements and various constraints.
  • Selection of most appropriate link, network and transport layer protocols.
  • Selection of most appropriate network architecture and network devices.
  • Network optimization techniques and algorithms, network reliability.
  • Performance measures.
  • Quality of service assurance.
  • Theoretical exercises and network design projects.
More »

DS-208 Ιnteroperability Systems [Opt/SDS] A. Prentza , E. Stougiannou

Learning Outcomes

The aim of this course is the familiarization of the students with the concept of systems interoperability, the understanding of basic concepts and the acquirement of essential knowledge in systems interoperability providing them with the ability to analyze and improve skills that will help them both in the scientific and professional field. The course introduces the students to fundamental principles of systems interoperability.

Course Contents

  • Introduction to systems interoperability
  • Basic principles, definitions and benefits
  • Main approaches and requirements
  • International Standards and Initiatives
  • European Interoperability Framework
  • Interoperability at organizational, semantic and technical level
  • Methodology for designing interoperable digital services
  • Interoperable public services
  • Interoperability in eProcurement
  • Interoperability in eInvoicing
  • Interoperability in eHealth
More »

DS-903 Human Factor Management [OPT/GEN] Faculty of the Department of BA, K. Poupouza

  • Course Code DS-903 Type of Course Opt./General
  • Theory/Lab Sessions 4 hours / 2 hours ECTS Credits 5
  • Semester 7th Semester FacultyFaculty of the Department of BA, K. Poupouza

This course offered by Department of Business Administration of University of Piraeus.

More »

DS-910 Business Policy and Strategic [OPT/GEN] Faculty of the Department of BA, K. Poupouza

  • Course Code DS-910 Type of Course Opt./General
  • Theory/Lab Sessions 4 hours / 2 hours ECTS Credits 5
  • Semester 7th Semester FacultyFaculty of the Department of BA, K. Poupouza

This course offered by the Department of Business Administration of University of Piraeus.

More »

DS-701 Educational Digital Systems [CSM/DS] D. Sampson

Learning Outcomes

With the completion of the course, the student will be able:

  • to know and understand the key concepts of exploiting digital technologies in teaching, learning and assessment of learning in K12 School Education.
  • to analyse, assess, select and justify a pedagogically appropriate educational technologies to support different teaching strategies in K12 School Education.
  • to design and create pedagogically grounded technology-supported teaching and learning scenarios for the K12 education.

The learning objectives of the course are aligned to the Greek State qualification framework for a teaching licence in K12 school education.

Course Contents

  • 1. Technology-Supported and Technology-Enhanced Teaching and Learning in School Education: Theoretical Underpinnings
  • 2. Integrating Technology in School Education (teaching, learning and assessment of learning): Models and Practice
  • 3. Taxonomy of Educational Technologies in School Education
  • 4. Educational Technologies for supporting different teaching and learning strategies
    • 4.1. Tutorials
    • 4.2. Drill and Practice
    • 4.3. Problem solving
    • 4.4. Modeling
    • 4.5. Virtual Labs and Simulations
    • 4.6. Inquiry-based Learning
    • 4.7. Collaborative Learning
    • 4.8. Assessment of Learning
    • o 4.9. Educational Games
  • 5. Digital School Infrastructure
    • 5.1. Interactive Boards
    • 5.2. ICT School Laboratory
More »

DS-706 Instructional Methods [OPT/GEN] F. Paraskeva, S. Retalis

Learning Outcomes

This course is designed to promote a fundamental understanding of the theoretical and applied knowledge related to instructional theories and models (principles, methods, strategies) for the design, development, implementation and evaluation of Technology Enhanced Learning Environments (TELE).

At completion of the course, the students will be able:

  • to describe the fundamental principles of instructional theories and models
  • to identify learners’ personal characteristics (learning styles, needs, motivations, attitudes) and how to apply them into educational practice (emphasizing on the processes by which individuals learn).
  • to apply these principles to learner – centered teaching.
  • to examine, analyze, design, develop and evaluate different types of instructional methods & strategies (discussions, lecturing, delivery media, support tools, collaborative learning, cases/simulations, etc.), for an effective teaching.
  • to demonstrate a knowledge of the ‘what’, ‘how’, and ‘when’, in the instructional design process in different disciplines.
  • to show mastery of various teaching methodologies.
  • to integrate ICT educational technologies into activities for K-16 and business settings.
  • to choose the appropriate institutional resources for the course/student development.
  • to show knowledge of the theory (Bloom’s Taxonomy etc) by designing lessons that utilize all levels of higher level intellectual/cognitive/metacognitive skills.
  • to implement teaching and presentation skills into educational and business setting.
  • to articulate strategies for addressing the needs of culturally diverse and special needs students. (
  • to create an educational plan/scenario for reflective thinking into educational practice.
  • to create the appropriate orchestrated instructional methods and strategies for an effective teaching.
  • to construct an integrated unit of instruction.
  • to provide the assignments (readings, case studies), individually and collaboratively (team effort).
  • to collaborate with classmates in designing instructional projects.
  • to show their ability to work with students one-on-one, in small groups, and in large groups through lab settings.
  • to articulate a personal set of values and a vision for their future classroom.

Course Contents

  • Introduction to the subject: Education – Learning – Instruction – Training.
  • the basic principles of the processing of learning (behavioral and cognitive approach, the cognitive and social constructivist theories in specific instructional methods).
  • the factors that influence instructional and learning outcomes (individual differences, self-efficacy beliefs, motivations, needs, attitudes, locus of control).
  • the personal and psychological factors in learning and instruction (learning styles, cognitive learning styles) and the implication on TELE (AHLE, smart education, e-portfolios, educational games, gamification).
  • the models of teaching and instructional design: Gagne’s Nine Events of Instruction, Piaget, Bruner, PBL, SRL, ADDIE Kirkpatrick model, MPI).
  • the taxonomies and learning objectives: design patterns/frameworks, methods, learning strategies, techniques, activities, evaluation (Bloom’s Taxonomy).
  • the formative, summative and authentic assessment.
  • the ICT in educational settings (synchronous and asynchronous learning, blended learning, flipped classroom, STEAM).
  • the ICT applications on instructional methodologies in educational and training settings (lesson plans, educational scenarios).
  • the applications using ICT in education (web 2.0 environments: wikis & blogs, LMS, web-based tools, authoring tools etc).
  • the school and professional environment, (interpersonal relationships, communication, ethics, etc).
  • socio-cultural politics of instruction (integrating different cultures).
More »

DS-330 Systems Simulation [Opt/T&N] A. Rouskas

Learning Outcomes

The course presents simulation techniques with particular emphasis on simulation of computer computational systems and communication networks. At the end of the course the students will be able to design models and develop simulation programs for the study and performance evaluation of complex computational systems and network communication.

Course Contents

  • Introduction to dynamic discrete event systems.
  • Development of discrete system models, event-advance design, time-advance design, activity-based design.
  • Pseudorandom number generation, random variables generation.
  • Overview of simulation languages and platforms.
  • Development of simulation programs using general purpose programming languages.
  • Measurement techniques, traffic load and experiment design.
  • Statistical analysis of simulation experiments, transient and steady state, data collection, confidence intervals, variation reduction techniques.
  • Simulation exercises and examples of data networks and cloud computing systems. Theoretical results verification.
More »

MAJOR IN "COMPUTANTIAL INFRASTRUCTURES & SERVICES"

Secondary Major in "COMPUTATIONAL INFRASTRUCTURES AND SERVICES": Compulsory Courses

DS-520 Ιntelligent Agents and Multiagent Systems [CSM/CAS] G. Vouros

Learning Outcomes

Upon successful completion of this course, students should be able to know principles, paradigmatic architectures and methods for developing single agent and multi agent systems, have a critical and informed view of strengths and limitations regarding agents and multi agent systems, towards designing and delivering such systems.

Specifically, students know and acquire the abilities to develop:

  • Architectures of single and multi-agent systems
  • Methods for agents coordination, collaboration and competition in specific settings and paradigmatic environments and problems
  • Agents’ communication methods and protocols

Via the critical view of agents technology and experience in developing such systems.

Course Contents

  • Agents: Principles, architectures and application examples
  • Deliberation vs Reaction: Architectures
  • Mental attitudes, states and their representation
  • Multi-agent Systems: Interactions and dependencies
  • Multiagent organizations and communication
  • Cooperation and collaboration
  • Agents communication
More »

Secondary Major in "DIGITAL SERVICES": Compulsory Courses

DS-701 Educational Digital Systems [CSM/DS] D. Sampson

Learning Outcomes

With the completion of the course, the student will be able:

  • to know and understand the key concepts of exploiting digital technologies in teaching, learning and assessment of learning in K12 School Education.
  • to analyse, assess, select and justify a pedagogically appropriate educational technologies to support different teaching strategies in K12 School Education.
  • to design and create pedagogically grounded technology-supported teaching and learning scenarios for the K12 education.

The learning objectives of the course are aligned to the Greek State qualification framework for a teaching licence in K12 school education.

Course Contents

  • 1. Technology-Supported and Technology-Enhanced Teaching and Learning in School Education: Theoretical Underpinnings
  • 2. Integrating Technology in School Education (teaching, learning and assessment of learning): Models and Practice
  • 3. Taxonomy of Educational Technologies in School Education
  • 4. Educational Technologies for supporting different teaching and learning strategies
    • 4.1. Tutorials
    • 4.2. Drill and Practice
    • 4.3. Problem solving
    • 4.4. Modeling
    • 4.5. Virtual Labs and Simulations
    • 4.6. Inquiry-based Learning
    • 4.7. Collaborative Learning
    • 4.8. Assessment of Learning
    • o 4.9. Educational Games
  • 5. Digital School Infrastructure
    • 5.1. Interactive Boards
    • 5.2. ICT School Laboratory
More »

Secondary Major in "COMPUTATIONAL INFRASTRUCTURES AND SERVICES" or "DIGITAL SERVICES": Optional Courses

DS-000 Compulsory Course of the Secondary Major that has not been chosen as compulsory course of Secondary Major [OPT/SM] -

DS-729 Energy and Environment Systems and Policies [OPT/GEN] I. Maniatis

DS-728 Learning Design [OPT/CIS] S. Retalis

DS-534 Algorithms for Electronic Markets [OPT/CIS] O. Telelis

Learning Outcomes

The course’s material includes the theory and practice that pertain to the design of economic mechanisms for automated trade exchanges, in modern digital platforms (auction websites, services provision and products retail websites, internet advertisement platforms). In particular, the course concerns the modern algorithmic techniques that facilitate the digital implementation of electronic markets.

Upon successful completion of the course, the students will be in position:

  • to understand the economic and algorithmic background that underlies the functionality of electronic markets.
  • to design electronic trade exchanges platforms, by choosing the appropriate economic mechanisms and the relevant algorithmic implementations.
  • to assess and evaluate the performance of economic mechanisms and their algorithmic implementations, relative to a given electronic market and its particulars.
  • to design, implement and evaluate automated pricing mechanisms.

Course Contents

  • Introduction to Game Theory: Strategies, Utility Functions
  • Strategic Games and Nash Equilibrium
  • Efficiency of Equilibria
  • Oligopoly Models
  • Auctions: First-Price, Second-Price, Multi-Unit Formats
  • Algorithmic Mechanism Design
  •  Sponsored Search Auctions
  • Combinatorial Auctions
  • Principles and Methods of Pricing
  • Prediction Techniques
  • Online Auctions
More »

DS-533 Data Processing Techniques [Opt/SDS] C. Doulkeridis

Learning Outcomes

The objective of this course is to familiarize students with: (a) learning access methods for large data volumes for various data formats, as well as scalable writing, (b) efficient data storage and retrieval with appropriate indexing techniques, (c) the design and implementation of data processing algorithms aiming at the development of efficient applications that manage data.

Upon successful completion of the course, the students will be in position:

  • to develop data-centric applications with emphasis in efficiency and scalability
  • to use the most appropriate indexing methods for a given problem
  • to evaluate and improve the parts of data processing algorithms that incur high computational load
  • to apply the most suitable data processing techniques that match with data under analysis and for a given query workload
  • to develop efficient data processing algorithms

Course Contents

  • Operation of disk and main memory, serial and random access, cost and efficiency, data locality on disk and main-memory, direct and indirect access, main-memory data structures (arrays, priority queues, hashing)
  • Data access techniques for structured, semi-structured and unstructured data: relational DBs, XML, RDF, text documents, web pages, web APIs, social networks.
  • One-dimensional data and indexing, B-tree, variations (B+tree, B*tree), range queries, inverted indexes.
  • Spatial data, spatial data types, spatial queries, approximation in representation, distance measures, extensions for multidimensional data.
  • Spatial indexing techniques, grid file, spatial indexes (R-tree, QuadTree), space-filling curves (Hilbert, Z-order)
  • Similarity search, k-nearest neighbor search, branch-and-bound algorithms, locality sensitive hashing (LSH), approximate k-nearest neighbor.
  • Top-k search: algorithms based on pre-processing, online algorithms, Fagin’s algorithm, index-based algorithms.
  • Join queries, spatial joins, top-k joins.
  • Spatio-textual data, query types, indexing methods, processing algorithms.
More »

DS-532 Advanced topics in data analytics [Opt/SDS] M. Halkidi

Learning Outcomes

The students after the successful completion of the course will be able:

  • to model and analyze data with appropriate analysis techniques, assess the quality of input
  • to choose the appropriate exploratory and/or inferential method for analyzing data, and interpret the results contextually.
  • to use supervised and unsupervised learning techniques for solving many analysis problems such as prediction, classification, segmentation.
  • to apply methods for the evaluation of the data analysis results.

Course Contents

  • Collection, preparation and representation of data for analysis
  • Linear, logistic regression
  • Classification Techniques (probabilistic classification, decision trees, support vector machines)
  • Predictive analytics and neural networks
  • Recommender systems
  • Graph analysis (applications on social networks)
  • Text mining – sentiment analysis
  • Evaluation of data analysis results
More »

DS-923 Information Systems Management [Opt/SDS] F. Malamateniou , E.L. Makri

Learning Outcomes

The main objective of the course is to introduce the fundamental concepts of digital systems project management and to study best practices in the area of project management such as the Project Management Body of Knowledge (PMBOK) of Project Management Institute (PMI), and to use such practices in project management of digital systems. The course will incorporate a laboratory session with project management software tools that allow students to practice some of the principles addressed.

Upon successful completion of the course the students will be able:

  • to recognize the need for IT project management
  • to recognize the key issues during the IT project management procedures
  • to describe the best practices in IT project management processes and follow an IT project management methodology –from project inception to project closure
  • to create work break down structures (WBS)
  • to create project plans
  • to create business cases
  • to describe PMI project management process groups
  • to use various methods and techniques for schedule and budget estimation
  • to use various methods and techniques for project monitoring
  • to use various methods and techniques for resource loading and leveling
  • to assign tasks and resources using project management software tools
  • to create a Gantt/PERT schedule using project management software tools
  • to monitor project progress using project management software tools

Course Contents

  • Introduction to project management (e.g. project definition, projects typology, triple constraint concept, a systems approach to project management, organizational influences).
  • Projects, information systems and services life cycles. IT project management methodologies (e.g. phases, deliverables, PMI project management procedures).
  • IT projects business cases (e.g. Measurable Organizational Value, feasibility study, risk analysis, cost-benefit analysis, financial and scoring models).
  • IT project management portfolios (e.g. project selection using Balanced Scorecard).
  • Project charters and project plans. PMI project management processes (PMBOK areas).
  • Project Time and Recourse Management (e.g. Work Breakdown Structure, Project organization structure and responsibilities, Gantt charts, the critical path, network diagramming, PDM networks, CPM/PERT, Scheduling with resource constraints).
  • Project estimation (e.g. Delphi technique, Time boxing). Software engineering metrics and approaches (e.g. Lines of Codes, Function point analysis, COCOMO).
  • Project control. Cost control (e.g. variance analysis, earned value). Performance analysis (e.g. Performances indices SPI and CPI). Forecasting (e.g. Forecasted cost to complete project, forecasted cost at completion).
More »

DS-513 Network Oriented Information Systems [CSM/IS] A. Niros

Learning Outcomes

The aim of this course is to explain the nature and basic characteristics of the Information Systems that are run and managed over a network. With the completion of the course, the student will be in position:

  • to understand and become familiar with the key aspect for the design and development of network-oriented information systems.
  • to know the main characteristics of the information systems, the required interfaces and the approaches to realize the network-oriented aspect of such information systems.
  • to be able to implement network-oriented information systems, by utilizing programming techniques and methods.

Course Contents

  • Information Systems and Networks.
  • Portals, Middleware, Integration, Enterprise Application Integration, Enterprise Service Bus.
  • Web Services, Service-Oriented Architectures, SOA governance.
  • Organizational change, the impact of integrated network oriented IS on organizations.
  • Enterprise Resource Planning applications, Customer Relationship Management systems, Supply Chain Management solutions, e-business applications.

Moreover, the EVDOXOS system is utilized to provide additional useful information to the students as well as exercises that respond to the corresponding thematic topics / sessions covered by the course.

More »

DS-703 e-Learning Systems [OPT/CIS] D. Sampson

Learning Outcomes

Upon successful completion of the course the students will be able:

  • to know and understand the key concepts of digital teaching and learning
  • to analyse, assess, select and justify pedagogically appropriate e-learning methods and tools for digital teaching and learning innovations.
  • to design and create pedagogically grounded online courses.

Course Contents

  • Online Teaching and Learning: Theoretical Underpinnings
  • Educational Design for Online Teaching and Learning
  • An hierarchical Open Access to Online Education framework: Elements (Open Educational Resources, Learning Activities and Lesson Plans, Online Courses, Digital Learning Spaces). Tools and Key Roles (Online Education Instructional Designers, e-Tutors, e-Learning Systems Administrators, Managers)
  • Open Educational Resources: Learning Objects, Educational Metadata, Repositories of Learning Objects. Case Studies: the National Repositories of Learning Objects
  • Learning Activities and Lesson Plans: Authoring Tools for Learning Activities and Lesson Plans, Repositories of Learning Activities and Lesson Plans. Case Studies: the National Repositories of Learning Activities and Lesson Plans
  • Design, Development and Delivery of Online Courses: Methodology for Designing Online Courses. Authoring Tools for Developing Online Courses. Course Management Systems. Case Study: Open edX, MOODLE
  • Digital Learning Spaces: 3D Virtual Classrooms and Laboratories
More »

DS-514 e-Business [Opt/SDS] A. Niros

Learning Outcomes

This course presents baselines on digital economy. With the completion of the course, the student will be in position:

  • to understand and become familiar with the key concepts and principles of applications of e-business.
  • to know the main characteristics of the e-business applications both in terms of development and in terms of provisioning of such applications.
  • to be able to implement e-business applications, by applying the knowledge obtained from laboratory exercises in different application contexts / domains.

Course Contents

  • e-Business introduction.
  • e-Commerce presentation.
  • Baselines on e-business micro-economy theory.
  • Business requirements analysis for the design of e-commerce.
  • Methodology for the design of successful web pages. Blogs.
  • e-Stores, methodology for the design of e-stores.
  • Design evaluation and faults detection through the use of web statistics applications.
  • eGovernment, ebanking; ehealth; business-to-business applications.

Moreover, the EVDOXOS system is utilized to provide additional useful information to the students as well as exercises that respond to the corresponding thematic topics / sessions covered by the course.

More »

DS-806 Cryptography [OPT/SEC] C. Xenakis , E.L. Makri

Learning Outcomes

The aim of this course is to support the students in learning the principles, concepts and applications of cryptography.
Upon successful completion of the course the student will be able:

  • to handle the basic elements of numerical theory and modular arithmetic
  • to manage cryptographic algorithms and their properties
  • basic cryptographic functions, such as pseudo-random sequences, one-way hash functions, shift and displacement networks and feistel networks.
  • the main features for symmetric and asymmetric cryptography are familiar
  • to handle key management systems and digital signatures

Course Contents

  • Basic definitions and concepts; information security.
  • Symmetric cryptography.
  • Digital signatures.
  • Authentication.
  • Public key cryptography.
  • Hash functions.
  • Integrity checking.
  • Key management and random number generators.
More »

DS-310 Wireless Sensor Networks [Opt/T&N] A. Alexiou

Learning Outcomes

The objective of this course is to focus on short range communications with emphasis on wireless local area networks (WiFi), adhoc networks, wireless sensor networks and applications.

At the end of this course, students will have acquired advanced/in depth knowledge in the field of Short Range Communications, with particular emphasis on baseband processing physical layer techniques, and Medium Access Control design.

The students will be capable of performing numerical calculations of various wireless parameters, stochastic modelling of wireless transceivers and performance assessment by means of analytical evaluations and simulations. The students will also be capable of comprehending the design principle of Wireless Local Area Networks and Wireless Sensor Networks of Internet of Things applications.

Course Contents

  • WiFi techniques, technologies, protocols and standards.
  • Short range communications: Personal Area Networks (PAN), Body Area Networks (BAN), Ultra Wide Band communications.
  • AdHoc Networks: Physical layer and transceiver design, MAC layer design, connectivity, topologies and routing.
  • Wireless Sensor Networks: Information-theoretic bounds on sensor network performance, detection and estimation, cooperative transmission, localization and positioning, energy efficiency.
  • Applications: eCommerce, safety, digital home, eHealth.
More »

DS-920 Student Placement [OPT/GEN] -

The students can choose it only once during undergraduate studies (either the 7th or the 8th semester).

More »

DS-313 Development of Telecommunication Systems [Opt/T&N] D. Georgiou

Learning Outcomes

The aim of this course is to familiarize students with best practices for the design and implementation of modern innovative telecom systems and applications. The main topics discussed include systematic multi-criteria requirement analysis, transformation of user requirements to architectural specifications and system functionality, design optimization for high performance and QoS, installation and deployment procedures, as well as system validation against initial requirements and specifications. The presented methodologies derive analytically from real case studies of innovative telecommunication systems and applications with extremely high added value and impact (e.g. the European Space Agency SATWAYS project in the field of Air Traffic Control). Students will further gain significant practical experience in the design and implementation of innovative telecommunication systems through exercise solving and development of small projects. Last but not least, the course presents an in-depth commercial feasibility analysis of the developed systems.

At the end of the course, students will be equipped with advanced expert and analytical knowledge for the consistent design, development and validation of innovative embedded telecommunication systems (see Course Content) meeting strict quality requirements regarding the provided telecommunication services. The obtained knowledge will allow the critical and analytical deepening as well as performing innovative research in the broad scientific domain of embedded telecommunication systems and applications.

Students will be capable of:

  • transforming user requirements to telecommunication systems architectural specifications and functionality.
  • specifying prototype embedded telecommunication systems, including their architectural layering (hardware, embedded software, software), according to specific QoS requirements for the provided services.
  • designing and specifying modern voice communication systems for next generation networks.
  • designing QoS models involving the end-to-end telecommunication transmission path from service provisioning to the end user, as well as extracting performance requirements and specifications for segments of the end-to-end transmission path.
  • optimizing the design of telecommunication systems for high performance and QoS.
  • explaining the details of the E-model adaptation and simplification of the discrete noise and advantage parameters in the demanding field of radio voice communications. The E-model (ITU-T Rec. G.107) is a transmission planning tool that provides a prediction of the expected voice quality, as perceived by a typical telephone user, for a complete end-to-end (i.e. mouth-to-ear) telephone connection under conversational conditions.
  • exploiting and solving the adapted voice QoS model for extracting system performance design parameters (e.g. for selecting appropriate voice codecs assuming a limited end-to-end delay and the constant values of delay parameters along the telecommunication transmission path segments).
  • compiling detailed plans for technical validation of system deliverables against the initial user requirements and system specifications.
  • analyzing the satellite link budget for the provisioning of telecommunication services and extracting requirements regarding the underlying telecommunication system.
  • analyzing the installation, deployment and operational details of the developed systems.
  • compiling workplans, work packages, time schedules, lists of technical deliverables and reports, critical paths, milestones and sample budgets involving R&D projects that design and develop innovative embedded telecommunication systems.
  • performing indicative techno-economic studies and commercial feasibility analysis regarding innovative embedded telecommunication systems, including a SWOT analysis (strengths, weaknesses, opportunities, threats).

Course Contents

  • Exemplary Innovative telecommunication systems and applications with high added value and impact.
  • Systematic multi-criteria requirement analysis.
  • Transformation of user requirements to architectural specifications and system functionality.
  • Design optimization for high performance and QoS.
  • Adaptation and validation of the E-model in the radio communications use case, including satellite transmission. The E-model (ITU-T Rec. G.107) is a transmission planning tool that provides a prediction of the expected voice quality, as perceived by a typical telephone user, for a complete end-to-end (i.e. mouth-to-ear) telephone connection under conversational conditions.
  • Exploitation of the voice QoS model for extracting system performance design parameters (e.g. for selecting appropriate voice codecs assuming a limited end-to-end delay and the constant values of delay parameters along the telecommunication transmission path segments).
  • Voice communications based on the NGN (Next Generation Network) standard.
  • Installation procedures and relevant issues.
  • System validation against initial requirements and specifications.
  • Commercial feasibility analysis.
  • Exercises and programming projects.
More »

DS-303 Satellite Communications [CSM/TEL] A. Kanatas

Learning Outcomes

The course provides the basic principles of cellular mobile communication systems. It also provides the methodologies of analysis and design of these systems. By concluding the course, students are able to analyze and design basic mobile communication systems by emphasizing in physical layer techniques. Specifically, students may recognize, describe and distinguish the characteristics of several type of cells, communication channels and multiple access techniques.

Moreover, ingredient components of a cellular system are described, and students are able to analyze and design systems with different requirements of telecommunication traffic and quality links. The analysis and design are based on the identification of several criteria, on the computation of thresholds of performance of links, on the comparison of alternative implementation plans and on the evaluation of the total performance of digital systems.

The lab sessions aim to provide a deeper understanding of physical phenomena of propagation in the wireless channel and the simulation of cellular systems.

Course Contents

  • Initially, basic concepts of Mobile Communications Radiosystems are provided (cell types, communication channel types, basic cellular system operations).
  • Next, the basic Network Access Techniques (Multiple Access Techniques, Random Access Techniques) are discussed.
  • Also, reference is made to the evolution of Wireless Communication Systems (1st, 2nd, 3rd, and 4th generation cellular systems, Wireless Telephony Systems, Paging Systems, WLANs, WPANs, PMRs).
  • Students are introduced to the concept of cells and frequency reuse (elements from regular hexagon geometry, cellular systems design).
  • Then the basic concepts of telecommunication traffic analysis and systems performance is provided (elements of Queuing Theory, Erlang B model, Erlang C model, spectral performance of cellular systems).
  • In the following the main wireless propagation mechanisms are presented (multipath propagation, Doppler fading and shift, propagation loss, shadowing, coverage area definition, radio channel capacity limits).
  • Also, interference types (co-channel interference and noise, neighboring channel interference) as well as handover and performance techniques (categorization of handover techniques, advantages and disadvantages of techniques, stable performance, dynamic performance, elastic performance) are discussed and compared.
  • Then techniques for improving spectral efficiency (sectoring, cell splitting) are analyzed.
  • Finally, elements and techniques of physical layer design (modulation and coding techniques, co-channel interference mitigation techniques) are presented and a presentation of standardized Mobile Communications Systems (GSM, GPRS, 3G and 4G) is presented.
  • In addition, extra content (in evdoxos.ds.unipi.gr) like articles, audiovisual lectures and Internet addresses, as well as exercises for student’s practice are posted electronically.
  • Case studies, exemplary problems and methods for solving them are presented.
More »

DS-331 Design and Optimization of Networks [CSM/NET] A. Rouskas

Learning Outcomes

This course targets on the design, evaluation and optimization of networks and services. The course is following the approach of top-down network design, that is most commonly encountered on medium to large scale networking projects. At the end of the course the students will be able to understand and evaluate alternative design options at every stage of data networks design, including requirement and specification definition, logical and physical design, selection of appropriate technologies and protocols, implementation, testing and optimization.

Course Contents

  • Introduction to the design and performance evaluation of networks and services.
  • Modelling and topological design of communication networks.
  • Modelling of network services traffic and work load.
  • Top-down network design under service requirements and various constraints.
  • Selection of most appropriate link, network and transport layer protocols.
  • Selection of most appropriate network architecture and network devices.
  • Network optimization techniques and algorithms, network reliability.
  • Performance measures.
  • Quality of service assurance.
  • Theoretical exercises and network design projects.
More »

DS-208 Ιnteroperability Systems [Opt/SDS] A. Prentza , E. Stougiannou

Learning Outcomes

The aim of this course is the familiarization of the students with the concept of systems interoperability, the understanding of basic concepts and the acquirement of essential knowledge in systems interoperability providing them with the ability to analyze and improve skills that will help them both in the scientific and professional field. The course introduces the students to fundamental principles of systems interoperability.

Course Contents

  • Introduction to systems interoperability
  • Basic principles, definitions and benefits
  • Main approaches and requirements
  • International Standards and Initiatives
  • European Interoperability Framework
  • Interoperability at organizational, semantic and technical level
  • Methodology for designing interoperable digital services
  • Interoperable public services
  • Interoperability in eProcurement
  • Interoperability in eInvoicing
  • Interoperability in eHealth
More »

DS-903 Human Factor Management [OPT/GEN] Faculty of the Department of BA, K. Poupouza

  • Course Code DS-903 Type of Course Opt./General
  • Theory/Lab Sessions 4 hours / 2 hours ECTS Credits 5
  • Semester 7th Semester FacultyFaculty of the Department of BA, K. Poupouza

This course offered by Department of Business Administration of University of Piraeus.

More »

DS-910 Business Policy and Strategic [OPT/GEN] Faculty of the Department of BA, K. Poupouza

  • Course Code DS-910 Type of Course Opt./General
  • Theory/Lab Sessions 4 hours / 2 hours ECTS Credits 5
  • Semester 7th Semester FacultyFaculty of the Department of BA, K. Poupouza

This course offered by the Department of Business Administration of University of Piraeus.

More »

DS-404 Pattern Recognition [CSM/DM] I. Maglogiannis , K. Moutselos

Learning Outcomes

Pattern recognition is the scientific field that deals with the assignment of a label to a given input value. An example of pattern recognition is classification, which attempts to assign each input value to one of a given set of classes. The course aims to cover the most popular in the literature techniques for pattern recognition, as they are typically employed in a number of practical applications, such as speech and audio recognition, image and video analysis, biometrics and bioinformatics. The course covers the most commonly used classification algorithms, feature selection techniques, data transformation methods, and data clustering.

Course Contents

  • Introduction to Pattern recognition systems
  • Parametric estimation of probability density function (maximum Likelihood estimation, maximum a posteriori
  • Bayesian classifiers and Bayesian Networks
  • k-nearest neighbor
  • Non parametric estimation of probability density function (Parzen windows)
  • Linear classifiers, non linear classifiers. Perceptron algorithm. Multilayer neural networks
  • Unsupervised Pattern recognition – Clustering
  • Feature generation: contour representation and contour tracing, chain code, polygon, signatures, linear transforms, Fourier Transform, regional features, image recognition, bias and variance, texture
  • Feature Selection and Kernels
  • Pattern recognition tools
More »

DS-706 Instructional Methods [OPT/GEN] F. Paraskeva, S. Retalis

Learning Outcomes

This course is designed to promote a fundamental understanding of the theoretical and applied knowledge related to instructional theories and models (principles, methods, strategies) for the design, development, implementation and evaluation of Technology Enhanced Learning Environments (TELE).

At completion of the course, the students will be able:

  • to describe the fundamental principles of instructional theories and models
  • to identify learners’ personal characteristics (learning styles, needs, motivations, attitudes) and how to apply them into educational practice (emphasizing on the processes by which individuals learn).
  • to apply these principles to learner – centered teaching.
  • to examine, analyze, design, develop and evaluate different types of instructional methods & strategies (discussions, lecturing, delivery media, support tools, collaborative learning, cases/simulations, etc.), for an effective teaching.
  • to demonstrate a knowledge of the ‘what’, ‘how’, and ‘when’, in the instructional design process in different disciplines.
  • to show mastery of various teaching methodologies.
  • to integrate ICT educational technologies into activities for K-16 and business settings.
  • to choose the appropriate institutional resources for the course/student development.
  • to show knowledge of the theory (Bloom’s Taxonomy etc) by designing lessons that utilize all levels of higher level intellectual/cognitive/metacognitive skills.
  • to implement teaching and presentation skills into educational and business setting.
  • to articulate strategies for addressing the needs of culturally diverse and special needs students. (
  • to create an educational plan/scenario for reflective thinking into educational practice.
  • to create the appropriate orchestrated instructional methods and strategies for an effective teaching.
  • to construct an integrated unit of instruction.
  • to provide the assignments (readings, case studies), individually and collaboratively (team effort).
  • to collaborate with classmates in designing instructional projects.
  • to show their ability to work with students one-on-one, in small groups, and in large groups through lab settings.
  • to articulate a personal set of values and a vision for their future classroom.

Course Contents

  • Introduction to the subject: Education – Learning – Instruction – Training.
  • the basic principles of the processing of learning (behavioral and cognitive approach, the cognitive and social constructivist theories in specific instructional methods).
  • the factors that influence instructional and learning outcomes (individual differences, self-efficacy beliefs, motivations, needs, attitudes, locus of control).
  • the personal and psychological factors in learning and instruction (learning styles, cognitive learning styles) and the implication on TELE (AHLE, smart education, e-portfolios, educational games, gamification).
  • the models of teaching and instructional design: Gagne’s Nine Events of Instruction, Piaget, Bruner, PBL, SRL, ADDIE Kirkpatrick model, MPI).
  • the taxonomies and learning objectives: design patterns/frameworks, methods, learning strategies, techniques, activities, evaluation (Bloom’s Taxonomy).
  • the formative, summative and authentic assessment.
  • the ICT in educational settings (synchronous and asynchronous learning, blended learning, flipped classroom, STEAM).
  • the ICT applications on instructional methodologies in educational and training settings (lesson plans, educational scenarios).
  • the applications using ICT in education (web 2.0 environments: wikis & blogs, LMS, web-based tools, authoring tools etc).
  • the school and professional environment, (interpersonal relationships, communication, ethics, etc).
  • socio-cultural politics of instruction (integrating different cultures).
More »

DS-330 Systems Simulation [Opt/T&N] A. Rouskas

Learning Outcomes

The course presents simulation techniques with particular emphasis on simulation of computer computational systems and communication networks. At the end of the course the students will be able to design models and develop simulation programs for the study and performance evaluation of complex computational systems and network communication.

Course Contents

  • Introduction to dynamic discrete event systems.
  • Development of discrete system models, event-advance design, time-advance design, activity-based design.
  • Pseudorandom number generation, random variables generation.
  • Overview of simulation languages and platforms.
  • Development of simulation programs using general purpose programming languages.
  • Measurement techniques, traffic load and experiment design.
  • Statistical analysis of simulation experiments, transient and steady state, data collection, confidence intervals, variation reduction techniques.
  • Simulation exercises and examples of data networks and cloud computing systems. Theoretical results verification.
More »