Course Description
The course material includes the following thematic areas:
- Introduction to the notion of entrepreneurship
- The eco-system of entrepreneurship
- Innovation and creativity
- Business idea – Business model
- Business plan (I): Development
- Business plan (II): Evaluation
- Software for the development of the financial statements of the business plan
- Foundation of the venture
- Managing and growing the venture
- Exit strategies
- Sources of capital and financing in all stages of growth.
- International entrepreneurship
- Social entrepreneurship
Learning Outcomes
The course aims to understand the concept of entrepreneurship, to acquire knowledge and skills regarding the entire cycle of the business process, from identifying the opportunity and its evaluation to mobilizing resources, creating the company and managing its development. The course also refers to the concept of social entrepreneurship and the development of social enterprises.
Course Description
The course deals with theory, algorithms and applications of discrete (also known as combinatorial) optimization with an emphasis on problems regarding flows, paths and matchings on graphs. More specifically, the course presents algorithms for the problems of shortest path, maximum flow, minimum-cost flow, maximum-cardinality and maximum-weight matchings (mostly regarding bipartite graphs) and, last, stable matchings and b-matchings on bipartite graphs.
Apart from solving such problems using specialized combinatorial algorithms, the students are also expected to formulate applications and real-life problems such as flow, path or matching problems on graphs. In addition, this course introduces general methods for discrete optimization problems that can be modeled as Linear Integer Programs, i.e., Branch-and-Bound and Branch-and-Cut.
The purpose of this course is the understanding of algorithmic design specifically for discrete optimization algorithms defined on graphs and integer programming methods. Apart from understanding all related notions, the purpose is to investigate the application of such algorithms (i.e., algorithms for paths, flows and matchings) on real-life problems.
The course material includes the following topics:
• Network Flows and Integer Programming
• Shortest-path algorithms: Dijkstra, Bellman-Ford, Floyd-Warshall
• Maximum-flow and minimum-cost flow algorithms
• Matching algorithms in bipartite graphs: maximum-cardinality matching, maximum-weight matching, stable matching and stable b-matching
• Applications modeled as flow problems: project management, job assignment to machines, distinct and restricted representatives, capital allocation, etc.v • Integer Programming: Branch-and-bound methods, Balas' additive algorithm, Branch-and-Cut methods
• Applications of Integer Programming
• Trees: properties, transversal algorithms, minimum-spanning tree algorithms, Steiner trees.
Learning Outcomes
Upon completion of this course, students will be able to:
- Describe and employ the fundamental concepts, the basic theorems of Combinatorial Optimisation.
- Perform the calculations for specific methods or algorithms of Combinatorial Optimisation for problems of reasonable scale, e.g., steps of max-flow algorithm, steps of integer programming.
- Model real-life problems arising from a variety of applications as Combinatorial Optimisation problems and identify the appropriate optimisation method or algorithm.
- Comprehend the proofs of relevant theorems and the broader mathematical foundations of Combinatorial Optimisation, use specific theorems (e.g., max-flow min-cut theorem) to resolve more effectively relevant problems and be able to explain and reproduce the most basic among these proofs.
- Study autonomously and in depth the current literature from academic journals and books of Combinatorial Optimisation, even in areas that marginally fall within the content of this course.
Course Description
Financial Engineering provides the means of implementing financial innovation using financial instruments like forwards, futures, swaps and options. Usual applications include the restructuring of corporate or investor cash flows to achieve tactical and strategic targets, with particular emphasis on risk management. Financial Engineering is at the forefront of innovation and development in financial markets, granting private investors, corporations and institutions almost complete flexibility in transforming existing cashflows into new cashflows with different quantitative and qualitative characteristics.
Learning Outcomes
This course aims to provide the tools, methodologies and skills necessary to understand, implement and innovate in this very active environment. Real case studies will be presented, demonstrating practical applications of the material taught.
Course Description
In this course, students learn to appreciate the opportunities and challenges from the use of ICTs, though in-class analysis and discussion of case studies from the international context, so that they can identify and manage similar situations efficiently when encountered in practice.
Students in this advanced course study how information systems in organizations can be managed so that information resources are efficiently used.
The course material includes the following thematic areas:
- Information sharing in organization
- Change management in the development and implementation of information systems (IS) in organizations
- Information resource management and IT department governance
- Broader information resource management issues (e.g. privacy) and their societal implications
- Strategic value and international growth trends for the IT sector
Learning Outcomes
Upon completion of the course, students will be able to:
1. Appreciate the challenges and main causes of failure in the use of information systems in organisations.
2. Utilize the appropriate knowledge background to understand the issues that management faces concerning information systems.
3. Understand the role of information systems in the context of a broader set of systems and relations withing business and society.
4. Develop the skill of understanding and analysing the current academic literature on information systems.
Course Description
Data warehousing, decision support, OLAP and data mining, what many people often call Business Intelligence (BI), has reached a maturity height with an abundance of systems, platforms and methods. It has evolved from a domain-specific area for large and highly sophisticated corporations, to an essential component of any modern business entity or institution. Although the field of BI is relatively new, the concept of using data to support decision-making is not. Performing complex data analysis and knowledge extraction over large volumes of data exists since the inception of information systems, in the form of executive information systems, statistical packages and artificial intelligence prototypes. The crucial difference between that era and today is the “democratization” of data analysis: by natively equipping DBMS with analytical capabilities and by providing practitioners with expressive data models, powerful integration tools and intuitive query languages, BI research brought to the masses clean, integrated and aggregated information in a timely manner.
Learning Outcomes
Upon completion of the course, students will be able to:
• Understand the benefits of data analysis for an organization
• Understand the different phases of data analysis
• Design the architecture and schema of a data warehouse
• Implement ETL processes in a data warehouse environment
• Create data cubes using a data warehouse
• Create multidimensional analysis/OLAP reports
• Use data visualization tools to produce dashboards
• Know basic data mining concepts: categorization, clustering, association rules
• Know NoSQL data management systems and their use in specific applications
• Understand what data streams are and how they are used for real-time analysis
• Use commercial or open source DB systems and visualization tools for all the above.
Course Description
Section 1: Self-diagnosis- Self-assessment
Section 2: Learning – Learning Styles
Section 3: Anxiety – Stress Management Techniques
Section 4: Dynamics and Group Processes
Section 5:Conflict and Negotiations
Section 6:Persuasion and Influence
Section 7: Development of Leadership Skills and Emotional Intelligence
Section 8: Career Strategy
Learning Outcomes
To be successful in the modern, constantly changing, organizational environment, the modern manager is required to possess abilities that are much broader than the narrowly defined technical knowledge and skills. The successful manager is no longer the one who possesses knowledge but the one who possesses the appropriate personal abilities and which he can use appropriately both with his colleagues and with himself. In this context, the course “Development of Personal and Leadership Skills” aims to help participants, first, to record, analyze, discuss their personal abilities and then to “improve” them, as much as possible, within a safe environment through a series of processes with a very strong element of interaction. In this way, participants will cultivate skills that will be particularly useful to them both in the search and development of their professional career and development.
Course Description
The course comprises two units.
Unit 1: E-Learning
• Workplace learning, employee performance and the role of technology: concepts, methods and tools
• E-learning platforms, technologies, and instructional content development tools
• Methods for digital instructional design
• Issues of eLearning Implementation and Management
Unit 2: Knowledge Management
• New Challenges – New Organizational Forms
• Knowledge Management: Definitions of notions, measuring intellectual capital, Types and forms of knowledge, Knowledge objects, Knowledge and competitiveness, Overview of tools for knowledge management
• Knowledge and Innovation
Learning Outcomes
This course offers an overview of the most recent trends in learning and knowledge management in companies and organizations. Students will be introduced to strategies, methods and technologies of organizational learning and knowledge management, helping them to develop analytical, development and judgmental skills. Students will be able to relate organizational and technological choices to performance improvements in organizations in the context of changing organizational environments. Practical skill in the implementation of e-learning programs and systems are also emphasized.
The course comprises two units; (1) E-Learning and (2) Knowledge Management.
In the first unit, students are introduced to concepts of organizational and workplace learning, training in the context of human resource development, and performance management. Methods and tools for digital instructional design are explained and then applied in practice by students in their course assignments.
In the second unit, after successfully completing the course, students will be able to:
1. Identify, describe and recognize different types of knowledge and different forms of knowledge in an organization.
2. Explain how types and forms of knowledge can be managed for organizational effectiveness and competitive advantages.
3. Combine enablers and knowledge management tools to design effective knowledge management structures.
4. Compare and evaluate approaches and knowledge management and KM systems using case studies.
Course Description
The purpose of the course is to understand issues related—directly or indirectly—to Enterprise Resource Planning Systems (ERP).
The course has both theoretical and practical orientation, aiming to familiarize students with related theoretical concepts on the one hand and the use of software solutions (SAP & NAV ERPs) that are globally widespread and adopted by companies and organizations across all economic sectors (industries) on the other.
Enterprise Resource Planning Systems (ERP) are a compact set of software applications that support a wide range of business activities and functions and serve as a business tool for controlling, monitoring, and coordinating operations in the central and remote facilities of a company. They achieve data centralization, the unification and integration of all a company's applications, and the redesign of business processes, aiming to optimize operations, increase productivity, and gain a competitive advantage using new information technologies. For modern businesses in the Information Society, ERPs are the core pillar of the transactional information infrastructure that enables companies and organizations to respond to the demands and challenges of economic activity within the framework of globalization.
The course is structured into the following units:
• Introduction to ERP systems
• Business Processes
• ERP Systems Implementation
• ERP Technological Infrastructure
• Production Planning and ERP
• Financial Management
• SAP ERP Introduction & case studies
• Microsoft NAV
The course content includes the following main thematic units:
• The product and the services it offers. The evolution of Enterprise Resource Planning (ERP) Systems. Technological overview with emphasis on modern approaches to system architecture. Representation of business events in database structures. The functionality offered by Enterprise Resource Planning (ERP) Systems. ERP systems as integrated information systems that support business processes.
• The implementation and application project. ERP systems as a turn-key project. ERP solution selection. Implementation methodologies. Critical success factors.
• The evolution of a 'live' system.
• The transition to E-Business, ERP software platforms and communities. ERP as a new channel for business communications. Extension of ERP systems for coordination of suppliers and customers of businesses. ERP software platforms and communities.
Learning Outcomes
The expected learning outcomes, upon completion of the course, are the acquisition of knowledge in the following key areas:
• The "ERP" product and the services it offers supporting business processes
• Factors and parameters of ERP implementation and application projects
• The evolution of ERP systems
• ERPs, e-business, ERP software platforms and communities: Contemporary trends in transition and transformation.
Course Description
The contents of the course cover the following thematic sections:
- Transport Systems: Components, structure and environment of a transport system, characteristics of supply and demand, performance measurement criteria and impacts of the operation of the transport system (energy, environment, safety).
- Transport Systems Planning Problems: Road Freight Transport Service Network Design Problem. Ship Fleet Composition Problem for the Provision of Regular Sea Transport Services (Liner Shipping). Strategic Traffic Planning Problem at Airports. Railway Transport Planning Problems
- Distribution Systems: Introductory concepts, definition of distribution systems, categorization of distribution systems, Distribution Centers and Warehousing. Case Studies.
- Distribution Systems Programming Problems: Multiple product distribution problem with direct shipments through a Transportation Network. Vehicle Scheduling and Routing Problem. Warehouse Location Problem. Warehouse Operations Programming Problems. Applications and Case Studies.
Learning Outcomes
Upon completion of the course, students will be able to:
Upon completion of the course, students will be able to:
- Understand the environment, structure, and operation of a transportation system.
- Understand the functions of distribution systems.
- Understand the characteristics of transportation and distribution system design problems.
- Develop mathematical models for the design and programming of distribution and transportation systems.
Course Description
• Introduction to Game Theory
• Stochastic Models in Operations Research
• Modeling of Discrete Systems
• Activity Cycle Diagram
• Simulation Methodologies
• Input Analysis
• Simulation and Industry 4.0Simulation Program
Learning Outcomes
Upon successful completion of the module "Stochastic Modelling and Simulation," students will have acquired both basic and advanced knowledge of the techniques of stochastic modelling and simulation. Specifically, they will be able to understand and apply methods of modelling and stochastic processes, such as Markov chains and Poisson processes. Furthermore, students will develop skills in using specialised simulation software (Simul8), be able to design and conduct simulation experiments, and analyse their results to make decisions under uncertainty. They will also acquire critical thinking and problem-solving abilities, enabling them to formulate and evaluate stochastic models in various management fields.
Course Description
The course includes the following sections:
• Introduction to Digital Marketing
• Digital Marketing Research
• Electronic Retailing and Digital Marketing
• Consumer Behaviour and Digital Marketing
• Integrated Digital Marketing Communications
• Electronic Customer Relationship Management (e-CRM)
• Strategic Digital Marketing Planning
• Digital Marketing and Sales
• Innovative Applications and Trends in Digital Marketing
• Special Topics in Digital Marketing
Learning Outcomes
Upon completion of the course, students will be able to:
• Obtain the necessary conceptual background in the Digital Marketing domain adopting an interdisciplinary approach.
• Recognize the research opportunities arising in Digital Marketing and obtain experience in designing and executing relevant research designs.
• Understand the basic usage dimensions of Digital Marketing applications in organizations and the main issues related to their effective exploitation.
• Obtain familiarity with the capabilities offered by Information Systems for the implementation of activities in the context of Strategic Marketing Planning.
Course Description
Knowledge of how capital markets work is essential to decision-making that involves raising and investing capital. Topics such as the risk-return relationship in investments, the structure of international money and capital markets, the efficient market hypothesis and the use of modern financial instruments are covered. Students are expected to have basic knowledge of mathematics, statistics and finance.
Learning Outcomes
The purpose of the course is to introduce the fundamentals of capital market theory and the basics of asset pricing and portfolio management. Real case studies will be presented, demonstrating practical applications of the material taught.
Course Description
The vast amount of available data produced by the interaction of users of online (and offline services) with systems and applications provides unprecedented opportunities to analyze, understand and predict human behaviour to deliver advanced and personalized services. Recently, the domain of Behavioral Analytics emerged as a response to the above need focusing on the exploitation of big data being produced mainly by the interactive online behaviour of users with fundamental goal to support users in the process of finding relevant and interesting information and at the same time to provide businesses the means to understand the needs of the customers predicting their future behaviour.
Learning Outcomes
Upon completion of the course, students will be able to:
- Understand human behavior modeling
- Understand data analysis algorithms
- Understand of personlaization applications in the business environment
- Develop skills for using data analysis tools
Ιn this course the students will acquire the skills required for applying Machine Learning techniques in practice. We cover the whole gamut of abilities and knowledge involved, from obtaining and working to data, to visualisation, interpreting data, different Machine Learning models and applications, up to and including Neural Networks and Deep Learning. The focus of the course is on the practical applied side, and students will work on projects using real-world tools widely used not just in the academia but in industry as well. This is not a computer science programming course, but students are expected to be proficient in the Python programming language, to be inquisitive and enjoy problem solving.
Course Description
Transformational change and innovation are key phenomena in today’s business environment. In this course we examine how and why firms strategically change and innovate. The aim is to provide students with the concepts and methodologies necessary to understand the complexities involved in these phenomena. We also focus on some key aspects of organisational life such as the organic link between innovation and strategy and the capacity of self-reflection during the process of innovation.
Learning Outcomes
Upon completion of the course, students will be able to:
• The changing environment and the ideal firm architecture
• Motors of change: Archetypal theories of change
• How do organizations adapt? The tempo of change
• Strategic Transformation from a practical perspective
• Innovation and Competitiveness
• Innovation processes
Students are expected to develop the necessary skills to allow them to design and implement strategic change and innovation initiatives