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Artificial Intelligence Applications
ΕΠ34 - Applications of Artificial Intelligence
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Applications of Artificial Intelligence
Course id: ΕΠ34
Type: Core Course
Semester: 7
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page: https://eclass.hua.gr/courses/DIT232/
Activities
Lectures (Theory): 3,0
Lab lectures: 0,0
ECTS credits: 5,0
Learning Outcomes
This course introduces students to the use of modern machine learning methods in Artificial Intelligence Applications. More specifically, the course focuses on on deep learning and its application in Computer Vision, Natural Language Processing and Reinforcement Learning problems.
General Skills
- Adaptation in new conditions
- Independent work
- Team work
- Decision making
- Promoting free, creative and deductive reasoningCourse Content
- Artificial Neural Network Training
- The Keras/Tensorflow deep learning framework
- Regularization
- Convolutional Neural Networks
- Image classification
- Visual object recognition
- Word embeddings
- Text classification
- Introduction to deep reinforcement learning and its applicationsLearning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
eclass course web page
use of AI frameworks and librariesCourse Organization
Assessment
- Final examination (60%)
- Assignments (individual or in teams) (40%)Literature
- Ian Goodfellow, Yoshua Bengio and Aaron Courville, “Deep Learning”, MIT Press, 2016 https://www.deeplearningbook.org/
- Charu C. Aggarwal, Neural Networks and Deep Learning: A Textbook, Springer, 2018
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, 2nd Edition, O' Reilly, 2019Journals (indicative list):
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Neural Networks and Learning Systems
Engineering Applications of Artificial Intelligence
Expert Systems with Applications
Journal of Machine Learning Research
Journal of Artificial Intelligence Research
Neural Computing and Applications
International Journal of Computer Vision
Conferences (indicative list):
Neural Information Processing Systems
International Conference on Learning Representations
AAAI Conference on Artificial Intelligence
Computer Vision and Pattern Recognition
International Conference on Computer Vision
International Joint Conference on Artificial Intelligence -
Assessment of ICT investments
ΕΠ23 - Technoeconomic Analysis of Information, Telematic and Telecommunication Systems
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Technoeconomic Analysis of Information, Telematic and Telecommunication Systems
Course id: ΕΠ23
Type: Core Course
Semester: 7
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page:
Activities
Lectures (Theory): 3,0
Lab lectures: 0,0
ECTS credits: 5,0
Learning Outcomes
General Skills
Course Content
Learning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
Course Organization
Assessment
Literature
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Basic Notions and Tools for DevOps
ΕΠ42 - Basic Notions and Tools for DevOps
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Basic Notions and Tools for DevOps
Course id: ΕΠ42
Type: Core Course
Semester: 6
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page:
Activities
Lectures (Theory): 3,0
Lab lectures: 0,0
ECTS credits: 5,0
Learning Outcomes
General Skills
Course Content
Learning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
Course Organization
Assessment
Literature
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Business Process Management in Suppply Chain
ΕΠ12 - Business Process Management in Suppply Chain
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Business Process Management in Suppply Chain
Course id: ΕΠ12
Type: Core Course
Semester: 5
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page: https://eclass.hua.gr/courses/DIT222/
Activities
Lectures (Theory): 3,0
Lab lectures: 0,0
ECTS credits: 5,0
Learning Outcomes
The course provides to students familiarity with the concepts, methodologies and tools for understanding the management of business processes, the benefits of automation and the impact of business processes on the performance and effectiveness of businesses/ organizations. The students apply in practice a language of business process modeling (BPMN – Business Process Modeling Notation). The course focuses on the supply chain processes, their impact, their evaluation and redesign with the purpose to improve the business operations and performance. The students will acquire the following knowledge and skills:
• Understanding of business process management methodologies and practices.
• Quantitative and Qualitative analysis of processes with the purpose to improve them.
• Analyzing and Modeling in practice As-Is processes and Proposing and Modeling To-Be processes
• Evaluation of alternative, new scenarios of business processes
• Understanding of supply chain processes
• Applying in Practice BPMN for business process management
• Utilization of BPM toolsGeneral Skills
- Search, analysis and synthesis of data and information with the use of the assorted technologies
• Decision Making
• Independent work
• Work at an interdisciplinary framework
• Project design and management
• Promoting reasoning and self-improvement
• Promoting free, creative and deductive reasoning
Course Content
- Lecture 1: Introduction to Business Process (BP) Management
• Lecture 2: BP identification (case studies)
• Lecture 3: BP modeling and redesign (methodologies, case studies)
• Lecture 4: BP Modeling language (BP Modeling Notation)
• Lecture 5: BP modeling diagrams, As-Is and To-Be models
• Lecture 6: Introduction to Supply Chain (Basics, Processes, Impact)
• Lecture 7: BP Analysis - KPIs, methods
• Lecture 8: Case studies of analysis and redesign of supply chain processes
• Lecture 9: Utilization of a BP modeling tool
• Lecture 10: Hierarchical BP modeling - Case studies
• Lecture 11: Quality in BP modeling
• Lecture 12: Qualitative and Quantitative Analysis of BP
• Lecture 13: BP transformation of supply chain processes utilizing state-of-the-art technologies (IoT, Data analytics, AI etc.)
Learning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
- Utilization of platform e-class
- Utilization of a business process modeling toolCourse Organization
Assessment
- Exams 50% • Assignment 50%
Literature
- Fundamentals of Business Process Management, Marlon Dumas, Marcello La Rosa,
Jan Mendling, Hajo A. Reijers. Springer, 2013.
● Business Process Management: Concepts, Languages, Architectures, Weske Mathias. Springer-Verlag, 2007.
● BPM CBOK Version 4. 0: Guide to the Business Process Management Common Body of Knowledge, Tony Benedict, Mathias Kirchmer, et al. 2019.
- Business Process Management Journal
• International Journal of Production and Operations Management
• International Journal of Production Economics
• International Journal of Production Research
• Supply Chain Management
- Search, analysis and synthesis of data and information with the use of the assorted technologies
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Compilers
ΕΠ33 - Compilers
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Compilers
Course id: ΕΠ33
Type: Core Course
Semester: 8
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page: https://eclass.hua.gr/courses/DIT107/
Activities
Lectures (Theory): 3,0
Lab lectures: 0,0
ECTS credits: 5,0
Learning Outcomes
The objective of this course is to teach students the theoretical foundations as well as the basic practical skills required in order to build compilers for a large number of programming languages.
Students will have the chance of building a large part of a compiler for a simple programming language.General Skills
Independent work
Team work
Promoting free, creative and deductive thoughtCourse Content
1st week (lecture): Introduction to Compilers. Phases of a Compiler
2nd week (lecture): Lexical Analysis
3rd week (lab): Lexical Analyzer for a calculator
4th week (lecture): Syntax Analysis. Top-Down Syntax Analysis
5th week (lecture): Bottom-Up Syntax Analysis
6th week (lab): Syntax Analyzer for a calculator
7th week (lecture): Syntax Directed Translation
8th week (lecture): Semantic Analysis
9th week (lab): Abstract Syntax Trees and Semantic Analysis for a calculator
10th week (lecture): Intermediate Code
11th week (lecture): Runtime Environment
12th week (lecture): Java Virtual Machine
13th week (lab): Generating JVM bytecode for a calculatorLearning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
eclass platform, youtube channel
Course Organization
Assessment
Oral Examination (100%)
Students build a full compiler for a simple programming language during the semester, and they are asked to demonstrate their work while answering questions.Literature
- Alfred V. Aho, Monica S. Lam, Ravi Sethi and Jeffrey D. Ullman. Compilers: Principles, Techniques, and Tools. 2nd edition. Addison-Wesley, 2007.
- Andrew W. Appel, Modern Compiler Implementation in C. Cambridge University Press, 1998.
- Andrew W. Appel, Modern Compiler Implementation in Java. Cambridge University Press, 1998.
- Κ. Lazos, P. Katsaros, Ζ. Karaiskos. Programming Language Compilers: Theory and Practice. Thessaloniki Publishers. 2004. In Greek.
- N. Papaspirou, E. Skordalakis, Compilers, Symmetria Publishers. In Greek. -
Cryptography
ΕΠ39 - Cryptography
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Cryptography
Course id: ΕΠ39
Type: Core Course
Semester: 8
Teaching and Examination Language: Greek
Is the course offered in Erasmus: No
Course web-page: https://eclass.hua.gr/courses/DIT208/
Activities
Lectures (Theory): 3,0
Lab lectures: 0,0
ECTS credits: 5,0
Learning Outcomes
This course will provide:
A first introduction on cryptographic definitions and notions
Familiarization with security issues
Understanding of the cryptographic protocols capabilities
The skills to select the most adequate cryptographic solutions for given security problem.General Skills
Search for optimal cryptographic solutions
Independent workCourse Content
Introduction to cryptography. History of cryptography and definitions
Mathematical background. Modular computations, Boolean functions, birthday paradox
Pseudorandom generators and stream ciphers
Pseudorandom functions, block ciphers and modes of operation
Differential and linear Attacks. Hellman’s method to invert one way functions. Attacks against stream ciphers.
One way functions and hash functions (MD5, SHA-1, SHA-2, SHA-3).
Message Authentication codes. HMAC and ECBC. Authenticated encryption schemes
Public key cryptography. RSA and secure implementations. The problem of factorization
El Gamal and elliptic curves. The discrete logarithm problem.
Digital signatures. Digital signature algorithm
Attacks against public key encryption protocolsLearning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
Course Organization
Assessment
Literature
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Database Design and Distributed Databases
ΕΠ03 - Database Design and Distributed Databases
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Database Design and Distributed Databases
Course id: ΕΠ03
Type: Core Course
Semester:
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page: https://eclass.hua.gr/courses/DIT128/
Activities
Lectures (Theory): 3,0
Lab lectures: 0,0
ECTS credits: 5,0
Learning Outcomes
The course aims to familiarize students with issues concerning the operation of databases and their efficient design. Such issues comprise: data redundancy, data integrity, query processing, security, recovery and concurrency control of transactions.
At the same time the objective is to improve the students' skills in programming languages for databases and teach them the basic concepts of data management and information mining from databases.
At the end of the course the students must be able to:
- Know the basic principles of database systems, the design process of a database.
- Engage in the collaborative design of a database that optimizes query execution
- Activate and manipulate the appropriate access control mechanisms, transaction management etc.General Skills
- Independent work
- Team work
- Adaptation in new conditionsCourse Content
Introduction to Database Design. Criteria for the quality of DB design. Functional Dependencies. Schema Normalization. Physical design. Storage and Indexing Structures. Query Processing and optimization. Transaction Processing, time-scheduling and serialization. Concurrency Control. Database recovery techniques. Distributed Databases and Databases on the Web. Object-oriented and Object-relational databases. Semi-structured data. Data warehouses and data mining.Learning and Teaching Methods - Evaluation
Teaching methods: - Face-to-face (lectures
& lab)
- Hands-on exercises
- AssignmentsUse of ICT:
- Specific software for query execution optimization
- Specific software for database programming
- Dissemination and organization of course material using OpenClass
- Communication via OpenClass and emailsCourse Organization
Assessment
The course grade takes into account
- the final exam grade (60%), which comprises
- Multiple choice questions
- Problem solving
- Critical evaluation of theoretical knowledge
- two or three compulsory assignments (40%), which are group and/or individual.Literature
- Fundamentals of Database Systems (5th Edition), R. Elmasri & S.B. Navathe, Pearson Higher Education, 2007
- Database Management System, R. Ramakrishnan/ J. Gehrke.. McGraw Hill. 2007
- Database System Concepts Fifth Edition, A. Silberschatz, H.F. Korth, και S. Sudarshan. McGraw-Hill, 2005.Journals
- VLDB Journal, ACM
- Transactions on Database Systems (TODS), ACM
- Transactions on Knowledge and Data Enginering (TKDE), ACM
- Data and Knowledge Engineering Journal (DKE), Elsevier.
- International Journal of Big Data Intelligence, Inderscience.
Conferences
- ACM SIGMOD
- ACM VLDB
- IEEE ICDE
- EDBT/ICDT
- ACM PODS -
Decision Support Systems
ΕΠ40 - Decision Support Systems
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Decision Support Systems
Course id: ΕΠ40
Type: Core Course
Semester: 7
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page: https://eclass.hua.gr/courses/DIT228/
Activities
Lectures (Theory): 3,0
Lab lectures: 0,0
ECTS credits: 5,0
Learning Outcomes
The main goal of the course is the undergraduate students to get acquainted with the decision-making systems both in theory and in practice. This course will provide a first overview of decision-making systems and methodologies as well as familiarize students with the basic decision-making simulation tools. An important goal of this course is the students to gain in-depth knowledge as well as skills that will make it easier for them to engage with decision-making systems at a professional level, emphasizing the needs of the market. For this reason, in addition to the theoretical lectures, students will be given the opportunity to solve practical exercises and laboratory simulations.
General Skills
- Independent Work
- Teamwork
- Adaptation to new situations
- Decision Making - Designing Decision Making Simulation Models - Experimenting with Decision Making Systems Simulation Models
- Promoting free, creative and inductive thinkingCourse Content
Decision Support Systems and Business Research - Types of Decision Making Problems - Decision Parameters - Decision Support - Decision Problem Categorization - Decision Making Process Phases - Decision Making System Components - Decision Making - Decisions - Architecture Decision- Methods of multi-criteria utility theory- Methods of superiority- Methods of multi-objective decision making or goalprogramming- Methods of analysis of preferences- Methods of "raw set" theory - Uncertainty in Decision Support Systems - Decision Making and Case studies -Simulation of Decision Support Systems
Learning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
-Open Source Software (Octave) -Eclass -Google meet
Course Organization
Assessment
Ι. Written final examination (60%)
ΙΙ. Semester Project assignments (40%)Literature
-ΣυστήματαΥποστήριξηςΑποφάσεων,Συγγραφείς:ΝικόλαοςΜατσατσίνης,ISBN:978-960-6759-44-4,EκδόσειςΝέωνΤεχνολογιώνΙδιωτικήΚεφαλαιουχικήΕταιρεία -ΠολυκριτήριεςΤεχνικεςΤαξινόμησης:ΘεωρίακαιΕφαρμογές,Συγγραφείς:ΜιχάληςΔούμπος,ΚωνσταντίνοςΖοπουνίδης,ISBN:960-209-449-4,Διαθέτης(Εκδότης):ΕκδόσειςΚλειδάριθμοςΕΠΕ -DecisionAnalysisforManagementJudgment,5thEdition,PaulGoodwin,GeorgeWright,ISBN:978-1-118-74073-6May2014496Pages
-Elsevier, Decision Support Systems -Elsevier European Journal of Operational Research (EJOR)
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Didactics of Infromatics
ΕΠ35 - Didactics of Infromatics
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Didactics of Infromatics
Course id: ΕΠ35
Type: Core Course
Semester: 6
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page:
Activities
Lectures (Theory): 3,0
Lab lectures: 0,0
ECTS credits: 5,0
Learning Outcomes
General Skills
Course Content
Learning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
Course Organization
Assessment
Literature
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Didactics of Robotics and STEM Training
ΕΠ43 - Didactics of Robotics and STEM Training
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Didactics of Robotics and STEM Training
Course id: ΕΠ43
Type: Core Course
Semester: 7
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page:
Activities
Lectures (Theory): 3,0
Lab lectures: 0,0
ECTS credits: 5,0
Learning Outcomes
The aim of the course is to help students to obtain fundamental knowledge about STEM field and educational robotics,
as well as the application of STEM technology and robotics in the school environment.General Skills
- Critical Thinking and problem-solving
• Team Work
• Accessing and analyzing information
Course Content
Learning theories and teaching strategies that can be used in STEM field. Design of teaching scenarios adopting STEM, educational activities in STEM, Educational Robotics, Teaching strategies using Robotics.
Learning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
eclass
youtube channelCourse Organization
Assessment
Presentation
Written ReportLiterature
"Educational Technology, Robotics Developing Platforms and IoT", Kalovrektis K., Ksenakis A., Psycharis S., Stamoulis G, Tziola Eds (in Greek)
"Teaching and Designing Educational Activities ISTEM and ICT", Psycharis S, Kalovrektis K, Tziola, Tziola Eds (in GreeK) - Critical Thinking and problem-solving
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Digital Image Processing and Applications
ΕΠ10 - Digital Image Processing and Applications
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Digital Image Processing and Applications
Course id: ΕΠ10
Type: Core Course
Semester: 6
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page: https://eclass.hua.gr/courses/DIT233/
Activities
Lectures (Theory): 3,0
Lab lectures: 2,0
ECTS credits: 5,0
Learning Outcomes
The course aims at introducing students to digital image processing technologies and methods, as well as its applications. The course will introduce students to:
- Image capturing and representation technologies
- Color theory and the various color models
- Core mathematical tools for digital image processing
- Methods for enhancement, segmentation and compression of digital imagesGeneral Skills
- Adaptation in new conditions
- Independent work
- Team work
- Promoting free, creative and deductive reasoningCourse Content
Image representation, Color Models, the RGB Model, Image Enhancement, Application of Filter Masks, Noise Reduction, Image Segmentation, Image Thresholding, Edge Detection, Image Compression.
Learning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
- eclass course web page
- use of specialized softwareCourse Organization
Assessment
- Final examination (60%)
- Assignments (individual or in teams) (40%)Literature
- R.C. Gonzalez, R.E. Woods, «Digital Image Processing», 4th Edition, Pearson, 2017.
- W. K. Pratt, «Digital Image Processing», 4th Edition, John Wiley and Sons Inc., 2007.
- J. S. Lim, «Two-Dimensional Signal and Image Processing», Prentice Hall, 1990.
- Ν. Papamarkos, «Digital processing and analysis of image », Giourdas Eds., 2005 (in Greek).IEEE Transactions on Image Processing
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Digital Satellite Communications
ΕΠ41 - Digital Satellite Communications
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Digital Satellite Communications
Course id: ΕΠ41
Type: Core Course
Semester: 5
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page:
Activities
Lectures (Theory): 3,0
Lab lectures: 0,0
ECTS credits: 5,0
Learning Outcomes
The objective of the course is to familiarize students with non-terrestrial networks such as satellites or
High Altitude Platforms, as well as their role in 5G. Reference is made to the necessary
theoretical background and emphasis is given on the understanding differences from the terrestrial
networks. Students come into contact with modern digital technologies and
those criteria on the basis of which, key components of a satellite telecommunications system are designed and selected.General Skills
-Retrieve, analyse and synthesise data and information, with the use of necessary technologies
-Adapt to new situations
-Make decisions
-Work autonomously
-Promoting free, creative and deductive reasoningCourse Content
The student will learn digital techniques such as APSK modulation, LDPC codes, Single/Multi Carrier schemes and multiple access techniques with Filter Banks. Simulation of the processing of the satellite signal to the transponder as well as the effect of non linearity of high power satellite amplifiers will be demonstrated, introducing students in the concepts of Software Defined Radio. Techniques for the improvement of the communication and compensation of the non-linearity will be taught. Simulation packages will be employed to model communication channels and demonstrate Beyond Line of Site Communications.
Learning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
Course Organization
Assessment
The course grade takes into account
- the final exam grade (60%), which comprises
- Multiple choice questions
- Problem solving
- Critical evaluation of theoretical knowledge
- one compulsory assignment (40%).Literature
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Economics of Digital Technology
ΕΠ37 - Economics of Digital Technology
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Economics of Digital Technology
Course id: ΕΠ37
Type: Core Course
Semester: 5
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page: http://eclass.hua.gr/courses/DIT194/
Activities
Lectures (Theory): 3,0
Lab lectures: 0,0
ECTS credits: 5,0
Learning Outcomes
The aim of the course is to acquaint students with the basic economic concepts and to relate them to the market of Information and Communication Technologies (ICT).
General Skills
Autonomous work, Adaptation to new knowledge and environments, Promotion of free, creative and inductive thinking.
Course Content
Basic economic concepts: Model and consumer and producer behavior. Supply and Demand Curves, Market Forms: Perfect Competition, Monopoly, Oligopoly. Indifference curves, income constraint, elasticities, production functions, scale returns, profit maximization, cost curves, economic prosperity, externalities. Complementary and substitute products. Applications and examples from the field of information technology and telecommunications. Introduction to game theory.
Learning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
Course Organization
Assessment
Literature
- Microceconomics, A modern approach , Varian Hal R.
- Economics (Microeconomics) , 4th Edition, Mankiw N. Gregory, Taylor P. Mark, Athanasios Maniatis, Anastasia Psiridou (ed)
- Microeconomics, Robin Bade, Michael Parkin -
Education Psychology
ΕΠ36 - Education Psychology
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Education Psychology
Course id: ΕΠ36
Type: General Knowledge
Semester: 8
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page:
Activities
Lectures (Theory): 3,0
Lab lectures: 0,0
ECTS credits: 5,0
Learning Outcomes
General Skills
Course Content
Learning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
Course Organization
Assessment
Literature
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Electronic Commerce and Economy
ΕΠ29 - Electronic Commerce and Economy
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Electronic Commerece and Economy
Course id: ΕΠ29
Type: Core Course
Semester: 8
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page:
Activities
Lectures (Theory): 3,0
Lab lectures: 0,0
ECTS credits: 5,0
Learning Outcomes
General Skills
Course Content
Learning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
Course Organization
Assessment
Literature
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Electronics Applications and IoT
EΠ246 - Electronic Applications in the Internet Of Things
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Electronic Applications in the Internet Of Things
Course id: ΥΠ07
Type: Core Course
Semester: 6
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page: https://eclass.hua.gr/courses/DIT125/
Activities
Lectures (Theory): 3,0
Lab lectures: 0,0
ECTS credits: 5,0
Learning Outcomes
The course is the basic introductory course in the design and analysis of electronic analog circuits used in computer science, telematics and the internet of things. Particular emphasis is placed on circuit implementation technologies that are key components of a modern computer circuit such as amplifiers, transistor gates, diodes, etc. At the same time, basic concepts of electronics such as Kirchoff's laws, input resistance and output concepts are presented. etc.
The course also contains a laboratory part which aims to familiarize students with the basic electronic circuits and their evaluation.
Upon successful completion of the course students will be able to:
a) Understand the basic concepts of electronic analog circuits.
b) To know the basic methodologies for amplifier design.
c) To know the basic methodologies for the analysis of diode circuits.
d) To perform response measurements in the various analog circuits.
e) To know the basic parameters of analog circuits and amplifiers.General Skills
- Independent work
- Team workCourse Content
Lectures:
1. Basic concepts of electronics
2. Kirchoff's laws
3. AC and DC analysis
4. General amplifier characteristics
5. Semiconductor diodes
6. Bipolar transistors I
7. Bipolar transistors II
8. Field effect transistors I
9. Field effect transistors II
10 Operational amplifiers
11. Microcontrollers
12. Sensors for IoT applications
13. System integrationLearning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
eclass, youtube channel
Course Organization
Assessment
Final written examination (100%)
Literature
1. L.S. Bobrow, “Elementary Linear Circuit Analysis”, 2nd Edition, New York Rinehart and Winston 1987
2. E.J. Kennedy, “Operational Amplifier Circuits: Theory and Applications”, New York, Holt Rinehart and Winston 1988
3. D. H. Navon, “Semiconductor Microdevices and Materials”, New York: Holt Rineh and Winston 1986
4. S. M. Sze, “Semiconductor Devices, Physics and Technology”, New York: 1985
5. P. E. Gray and C.L. Searle, “Electronic Principles”, New York Wiley 1971
6. P.R. Gray D.A. Hodges and R.W. Brodersen, “Analog MOS Integrated Circuits", New York: IEEE Press 1980
7. T. Wayne, “Advanced Electronic Communications Systems”, Pearson Educations, Limited, 2003
8. P. Horowitz, W. Hill, “The Art of Electronics”, Cambridge University Press, 1989Electronics Letters, IET
IEEE Transactions on Electron Devices -
Informatics and Education
ΕΠ225 - Informatics and Education
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Informatics and Education
Course id: ΕΠ225
Type: Core Course
Semester: 5
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page:
Activities
Lectures (Theory): 3,0
Lab lectures: 2,0
ECTS credits: 5,0
Learning Outcomes
General Skills
Course Content
Learning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
Course Organization
Assessment
Literature
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Internet Technologies
ΕΠ13 - Internet Technologies
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Internet Technologies
Course id: ΕΠ13
Type: Core Course
Semester: 5
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page:
Activities
Lectures (Theory): 3,0
Lab lectures: 0,0
ECTS credits: 5,0
Learning Outcomes
The course seeks to familiarize students with the TCP/IP layered approach and the investigation on all internet related protocols, starting from the highest TCP/IP layers.
General Skills
- Independent work
- Team workCourse Content
Internet Architecture. Quality of Service in the Internet. Resource Reservation Protocol (RSVP). Integrated Internet Services Architectures, Differentiated Internet Services Architectures. Packet Scheduling, Bandwidth Brokers, Multi-protocol Label Switching (MPLS). Internet Security (IPSec, PKI). Service provisioning and call control through open interfaces (JAVA APIs, JAIN, Parlay architectures). Distributed object technologies (DOT, CORBA, RMI, SOAP). The role of object-oriented design techniques and software development in communications (network management systems, IN, active, autonomous networks, etc). Mobile Intelligent Agent Technology. Service Description Languages. Service Modelling Tools. Applications in the WWW.
Learning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
e-class utilization
Course Organization
Assessment
Final written examination (100%)
Literature
WEERAWARANA, CURBERA, LEYMANN, STOR, "Web services Platform Architecture "
IEEE Systems, IEEE Access
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IT Project Management
ΕΠ31 - IT Project Management
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: IT Project Management
Course id: ΕΠ31
Type: Core Course
Semester: 8
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page:
Activities
Lectures (Theory): 3,0
Lab lectures: 0,0
ECTS credits: 5,0
Learning Outcomes
General Skills
Course Content
Learning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
Course Organization
Assessment
Literature
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Management of Software Defined Networks
ΕΠ44 - Management of Software Defined Networks
General Information
School: Digital Technology
Department: Informatics and Telematics
Level: Undergraduate
Course Title: Management of Software Defined Networks
Course id: ΕΠ44
Type: Core Course
Semester: 8
Teaching and Examination Language: Greek
Is the course offered in Erasmus: Yes
Course web-page:
Activities
Lectures (Theory): 3,0
Lab lectures: 2,0
ECTS credits: 5,0
Learning Outcomes
The aim of the course is to acquaint students with the basic management models of fixed and wireless / mobile communications, as well as the basic mechanisms for the design, development and evaluation of Network Management Systems. Upon successful completion of the course the student will be able to:
• gain an overview of methodologies, techniques, technologies and protocols for monitoring, managing, controlling, optimizing performance and designing computer networks
• proposes solutions for the initial design, expansion and upgrade of networks in the context of specific business objectives and technical requirements / problems, as well as for monitoring the implementation of specific technical requirements through a service agreement (SLA).
• practice in the application of taught protocols for the monitoring of the operation of network data within the laboratory of the courseGeneral Skills
Individual assignment, project work
Course Content
Overview of integrated voice-data application networks - Internet / Intranet architecture video and digital telephone networks
• Management needs (operational, administrative, analytical / regulatory, long-term planning)
• OSI Reporting Structure Management, Troubleshooting, Administration and Network Security
• Management of TCP / IP networks (Internet type), SNMP protocol, Internet routing
• Web-based management
• Examples of integrated management systems (HP - Openview and CISCOWorks)
• Physical and line level function management (modulators, Ethernet and ATM switches, transmission lines)
• Management of digital telephone networks (OA & M) and broadband networks of integrated applications, the TMN standard
• CCS 7 and ISDN common channel signaling, Intelligent Network services.
• Virtual Private Networks defined by software.Learning and Teaching Methods - Evaluation
Teaching methods: face-to-face
Use of ICT:
Course Organization
Assessment
Written final examination (100%)
Literature
Sudhir Dixit, Ramjee Prasad, Wireless IP and Building the Mobile Internet (Artech House Books, 2003)
Nathan Muller, LANs TO WANs: The Complete Management Guide, (Artech House Books, 2003)IEEE Communications magazine, IEEE VTM, IEEE Transactions on Communications
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