Τμήμα Εφαρμοσμένης Πληροφορικής
Σχολή Επιστημών Πληροφορίας

Program of studies




acad.year 2015-2016

Applied Informatics - Technology Management: 1st year
[Semester 1] [Semester 2] 
AI - Applied Informatics
[Semester 3] [Semester 4] 
[Semester 5] [Semester 6] [Semester 7] [Semester 8] 
TM - Technology Management
[Semester 3] [Semester 4] 
[Semester 5] [Semester 6] [Semester 7] [Semester 8] 

Semester 6
Study Direction: AI - Applied Informatics   


ARTIFICIAL INTELLIGENCE (ΠΛ0701) up.gif
Refanidis Ioannis     

Objective
To be able to: (a) model search problems and use suitable search algorithms to solve them; (b) represent knowledge and reason over it; (c) model and solve planning problems.
Content
Intelligent agents.
Search algorithms. Blind search and informed search.
Constraint satisfaction problems.  Arc consistency. Constraint propagation.
Adversary games. Minimax search and alpha-beta pruning. Games with chance.
Knowledge and reasoning. Propositional logic. First order logic. Resolution. Ontologies. Semantic web.
Planning. STRIPS representation. Progression and Regression. Partial order planning. Temporal planning and planning with resources.



DECISION SUPPORT SYSTEMS (ΠΛ0805-1) up.gif
Hristu - Varsakelis Dimitrios     

Objective
The course aims to a) expose the basic features of a decision support system (DSS) and b) show students how to formulate small-scale decision support models that could serve as the “core” of a DSS. We will discuss various techniques and tools from applied mathematics and optimization in order to solve a series of practical decision problems.
Content
Introduction to Decision Support Systems (DSS) – structure of DSS
Introduction to Decision Theory
Decision Trees
Utility theory
Multicriteria Decision-making
Introduction to discrete-time dynamical systems
Markov-based models
Dynamic Programming



ECONOMETRICS II (ΠΛ0709) up.gif
Dritsakis Nikolaos     

Objective
Upon completion of this course, students should be able to:(a) Understand the basic principles of Econometrics II(b) Identify the main theories of Econometrics II(c) Apply the methodologies of Econometrics II on real cases(d) Use the tools of Econometrics II in decision - making
Content
- Models with dummy variables (functional relocation, functional rotation, simultaneous functional relocation and rotation, simultaneous use of more than one qualitative explanatory variables, Use of dummy variables in seasonal analysis)
- Combining cross-section and time-series data (cross-section heteroscedasticity, cross-section independence and time-series autocorrelation, cross-section heteroscedasticity, cross-section correlation and time-series autocorrelation)
- Distributed-lag models (DLM) (Estimation of DLM, Estimation of DLM under restrictions with limited or unlimited number of lags, empirical DLM, methods of estimation of DLM with unlimited number of lags, diagnostic tests, and applications)
- Simultaneous equation models (simultaneous equations bias, identification, methods of estimation (indirect least squares, two-stages least squares), seemingly unrelated equations, diagnostic tests, model analysis)



INFORMATION AND SYSTEMS SECURITY (ΠΛ0713-2) up.gif
Mavridis Ioannis     

Objective
The student will (a) learn the fundamental issues and principles of information and systems security, (b) gain familiarity with theoretical background like security models and policies, (c) acquire knowledge and experience on basic protection techniques and new directions on developing secure information systems.
Content
Introduction (Fundamental concepts, Security breaches, Vulnerabilities, Threats, Control measures, IS security requirements, Privacy protection)
Personal Computers Security - Malicious Code (Viruses, Warms, Trojan Horses)
Identification and Authentication (Techniques, media, standards, procedures and issues, Implementations in common operating systems)
Access Control (Discretionary, Mandatory, Role-based, Extensions and Implementations in common operating systems)
IS Security Models and Policies (Clark-Wilson, Harrison-Ruzzo-Ullman, Graham-Denning, Chinese Wall, Bell-La Padula, Biba, High-Level Security Policies).
Risk Analysis and Assessment (Theoretical approaches, Application examples, Cramm and Cobra tools)
Computer Systems Security Evaluation (TCSEC criteria, ITSEC criteria, Federal criteria (FF), Common Criteria (CC))
Database Systems Security (Components and security domains, Implementations in the DBMS of ORACLE)
Mobile Computing Systems Security (Mobile computing systems infrastructure configuration, classification of security parameters, security mechanisms and standards)



INFORMATION TECHNOLOGY LAW (IT LAW) (ΠΛ0617) up.gif
Alexandropoulou Evgenia     

Objective
The aim of this course is to familiarize students with the legal framework of personal data protection, including the rules governing their electronic processing, as well as with the legal framework of intellectual rights in digital environment.
Content
Content
Part I: Electronic processing of personal data (Legal framework/ Simple and sensitive personal data/ Obligations of data controllers/ Rights of data subjects/ Sanctions/ The Data Protection Authority)
Part II: IT and intellectual property. Historical background of copyright law/ The necessity of legal protection of copyright in the modern digital environment/ Modern legal environment of copyright / Legal protection of computer programmes, databases, multimedia/ Copyright transfer/ Right owners/ Right enforcements and sanctions/ Right collective management organizations/ Intellectual Property Organization