<span class="multilang" lang="el">Μαθηματικός Προγραμματισμός</span><span class="multilang" lang="en">Mathematical Programming</span>

Mathematical Programming

This course examines the theory and the algorithms of Mathematical Programming and their relations to other areas (e.g., Game Theory). In particular, the course includes the Linear Programming problem, Duality Theory, basic algorithms for Linear Programming, introductory concepts of Non-Linear Programming and Integer Programming, problem formulation in Mathematical Programming, Dynamic Programming and Linear Programming's relation with Game Theory. The expected outcome is the solid understanding of all the above and, in addition, the applications of Mathematical Programming arising from real-life settings. More specific outcomes include the in-depth knowledge of mathematical structures and properties of classes of problems, the use of algorithms but also the design of variants for special cases and, last, the modeling and solving of relevant practical problems.
The purpose of this course is the in-depth understanding of the theory and applications of Mathematical Programming. More specific learning outcomes include:
I. The understanding of mathematical structure and properties of fundamental problem classes (e.g., linear, non-linear and integer programming, dynamic programming)
II. The use of Mathematical Programming algorithms for problem solving but also the design of their variants for special problem cases.
III. The formulation and solving of problems arising from practical, real-life settings.

Course contents

The course material includes the following topics:
- The Simplex Method: description, geometric interpretation and special cases
- Sensitivity analysis and economic meaning
- The Karush-Kuhn-Tucker conditions, description and proof
- Duality Theory
- Introduction to Non-Linear Programming
- The transportation problem and the Network Simplex Algorithm
- Model building and formulation, applications and case-studies
- Integer Programming, modeling and solution methods
- Linear Programming and Game Theory
- Dynamic Programming: formulations, solution approach and applications

<span class="multilang" lang="el">Χρηματοοικονομική Διοίκηση</span><span class="multilang" lang="en">Financial Management</span>

Financial Management

The objective of the course is to introduce the student of management science to the fundamentals of financial management. To this end, the course revolves around the functions of the financial system, the concept of time value of money, corporate investment and financing decisions, investment appraisal criteria and security pricing. Students will get a chance to test their understanding of the concepts and tools covered in lectures via either an elective group coursework or a real business case study.

Course contents

The course material includes the following thematic areas:

  • The financial system
  • Time value of money
  • Investment evaluation criteria
  • Risk and return of investment
  • Asset pricing
  • Financing decisions and the efficiency of capital markets

<span class="multilang" lang="el">Διαχείριση Ανθρωπίνων Πόρων</span><span class="multilang" lang="en">Human Resource Management</span>

Human Resource Management

The course aims to develop the conceptual and theoretical background of today’s Human Resource Management (HRM). The course’s main objectives are:
- Understanding the importance of Human Resources as the strategic factor of sustaining business success.
- Understanding the main issues of HRM in today’s complex and dynamic environment.
- Learning the concepts, the theories and the tools to deal with all-important HRM issues.

Course contents

- Introduction to HRM
- Job Analysis
- Human Resource Management Planning
- Recruiting-Selection
- Performance Appraisal
- Reward System and motivation
- Training and Development
- Internal communication
- Change management
- Organizational learning and Learning Organization
- Managing culture

<span class="multilang" lang="el">Ανάλυση και Σχεδιασμός Πληροφοριακών Συστημάτων</span><span class="multilang" lang="en">Analysis and Design of Information Systems</span>

Analysis and Design of Information Systems

The course aims to respond to the organizational need to identify and understand problems in the management of information and processes. In this course students are exposed to methods for the systemic and systematic study and modeling of such problems, so that they can be supported by information systems. The course focuses on the identification, modeling and documentation of requirements of the various users and stakeholders that influenced and are influenced by the development of information systems. The transition from requirements to functional specifications, information system design and the development and implementation plan in the organization that will use the information system are also studied. Particular emphasis is given on the role of the human agent in information systems development. The practical part of the course concerns the analysis and design of information systems using tools such as Soft Systems Methodology (SSM), the Unified Modeling Language (UML) and the website design language HTML.

At the end of this course, students will be able to understand the information systems development process and have the essential theoretical and practical knowledge necessary for its effective management.

Course contents

The course material includes the following areas:
1. Introduction to organizational information systems
2. Human activity systems modeling
3. Information systems analysis
4. Information systems design
5. IS life cycle – Rational Unified Process (RUP) – IS development methodologies
6. The information system in the organization (implementation and evaluation)

<span class="multilang" lang="el">Αλγόριθμοι και Δομές Δεδομένων</span><span class="multilang" lang="en">Algorithms and Data Structures</span>

Algorithms and Data Structures

The course aims to present students with the basic principles and techniques of algorithms, and data structures, focusing on real problems.

Students will:
- Understand how algorithms and data structures are used in solving real world problems.
- Consider trade-offs in solving computing problems.
- Come in contact with cryptographic principles governing all digital communications and transactions.
- Learn techniques that are used in solving problems involving big data, in different application areas.

Course contents

- Algorithms and Complexity
- Data Structures
- Graphs and Networks
- Cryptography