The course aims to introduce students to the basic statistical concepts and the analytical procedures used in quantitative research in economics and business administration. Students should understand basic principles of Probability Theory and Statistics to be able to apply basic statistical methods. By the end of the course the students will be able to process data, prepare tables and charts and present and analyze statistical results. 

The course aims to familiarize students to the basic concepts of limit, continuity, differentiation and integral. Furthermore, the course purposes to introduce student to the theory of optimization and help them to understand appropriate mathematical methods that will lead them to study and solve economic, administrative and other problems using mathematical analysis.  

The main goal of this module is to familiarize students with the main principles of software development. Using Java which is perhaps the most popular high level programming language, students will be taught about the object-oriented programming practices with particular emphasis placed on coherent software design, code reuse and the exploitation of existing libraries.

In the last decade the demand for programming skills related to managing and visualizing data has grown remarkably. Python, R and SQL feature consistently in the top skills listed in data science and data analyst jobs. Knowing how to write efficient software code to handle and visualise data is an essential skill for any modern data scientist. This course will cover the main principles of computer programming with a focus on data science applications by following the entire pathway from raw data to databases, data wrangling and visualisation, machine learning frameworks up to software development.

The general objective of this 4-ECTS credit (European Credits Transfer and Accumulation System) required degree level course is to enable students to communicate competently at a Β1-B2 level of the Common European Framework of Reference (CEFR) for Languages. It is particularly designed to meet the needs of university students studying in the field of Data Science. The course is designed to equip students with the necessary language skills and specialized vocabulary required to effectively communicate and work in the field of data science for economics and business. This course focuses on developing proficiency in English language usage, technical writing, and oral presentation skills specifically tailored for data science professionals. Through a combination of interactive lectures, practical exercises, and hands-on projects, students will enhance their ability to comprehend, interpret, and communicate complex data-related concepts in English. The course will cover various aspects of data science, including data analysis, statistical modeling, machine learning, and data visualization, while emphasizing effective communication within interdisciplinary teams and across different stakeholders. Throughout the course, students will have the opportunity to apply their language skills to real-world data science scenarios, work on collaborative projects, receive feedback on their communication abilities, and engage in discussions on ethical and professional practices in the data science industry.

Matrix analysis and computations are widely used in many data science fields such as multivariate statistics, econometrics, machine learning, optimization, and many more.  They are considered key fundamental tools.
The course is designed to provide the students with sufficient knowledge in mathematical and algorithmic tools for matrix problems which is essential to understand advanced topics related to their subject. It also aims to enable students to apply these mathematical techniques, solve various problems using specialised software and to help them develop and enhance their critical thinking. The course includes a laboratory in MATLAB (or Octave), R and Python.

The course is designed to provide the students with sufficient knowledge of statistics which is essential to understand advanced topics related to statistics. It covers topics related to random variables, covariance/correlation, central limit theorem, method of moments, maximum likelihood, distributions, hypothesis testing, regression analysis, etc. 

The Internet Applications Programming module enables students to extend their knowledge in Java and object-oriented programming techniques and obtain experience in designing and developing a complete networked system. Of particular interest are concepts such as inheritance and concurrent programming as well as the technologies used to access remote servers and databases. Moreover, students will design and develop a Graphical User Interface utilizing the Java software libraries readily available.

This module aims to provide training in the basic skills of practical statistics using a statistical software package. Furthermore, provides the foundation for further study of statistics. Upon completion of this module, students are expected to able to:
•    to use the R statistical software package and python for data analysis and simulation;
•    to identify and carry out an appropriate statistical analysis of a simple data set using a computer;
•    to interpret the output from a statistical software package when used for simple statistical analyses.

The general objective of this 4-ECTS credit (European Credits Transfer and Accumulation System) required degree level course is to enable students to communicate competently at a B2 level of the Common European Framework of Reference (CEFR) for Languages. The course is designed for individuals who have a solid foundation in English language skills at B1 level and wish to further refine their communication abilities in the specialized field of data science. Building upon the concepts covered in the introductory course, this higher-level course delves deeper into advanced language usage, technical writing, and oral presentation skills, focusing specifically on the complex and evolving aspects of data science. Through a combination of advanced lectures, hands-on projects, case studies, and interactive discussions, students will engage with cutting-edge topics in data science, exploring advanced statistical modeling, economics, deep learning, natural language processing, and ethical considerations in AI. The course aims to equip students with the language proficiency and communication strategies necessary to navigate the complexities of advanced data science concepts and effectively communicate them to diverse audiences.

Microeconomics is a key pillar of Economics and therefore the scientific training of every economist. In particular, this course presents and analyzes the elementary tools of economics in order to better understand and apply the economic theory.
Students will develop economic thinking and will be able to use basic economic principles and tools to analyze markets and evaluate economic policies.

The aim of the course “Principles of Macroeconomics” is to provide an extensive introduction to macroeconomic theory as well as answers to questions concerning the economy as a whole.
More specifically, the initial objective of the course is to understand basic macroeconomic concepts such as national income, inflation and unemployment as well as to understand the determinants of economic growth and productivity. An additional and equally important objective of the course is to help students understand the functioning of the financial system as well as the role of the central bank in the exercise of monetary policies.
Finally, the course aims to introduce students to basic concepts of the open economy including that of the exchange rate as well as the investigation of short-term fluctuations in the economy.
After completing the course, students will be able to understand and recognize the macroeconomic problems that concern an economy, as well as understand how the economy works at a macro-level, in the short-term and int the medium-term.

The aim of the course is to acquaint the students at an introductory level with the subjects dealt with by the science of accounting. Specifically, the course will give students a general idea of what financial accounting is with a general development of the concepts of assets, liabilities, double-entry method and the regulatory and conceptual framework regarding accounting. Students will learn to prepare and interpret a balance sheet, account reconciliation statement, income statement, cash flow statement and interpret numeral ratios.
The ultimate goal is to provide an overview of key financial statements, their content and their usefulness in decision making process.

The main objective of the course is to learn the basic elements of computational optimisation theory, numerical algorithms, and their applications. This course aims to introduce students to linear programming (simplex method, duality theory), numerical methods for solving non-linear optimisation problems, unconstrained optimisation problems (optimality conditions, descent algorithms and convergence theorems), and problems with constraints (Lagrange multipliers, Karush-Kuhn-Tucker conditions, active set, penalty and interior point methods). It also aims to equip students with the ability to determine necessary and sufficient optimisation conditions for different classes of optimisation models and to apply the appropriate numerical methods given the characteristics of the optimisation model. Applications in engineering, economics, statistics, and other fields will be emphasized. Students will also use MATLAB or R to gain hands-on experience with the material. 

This is an introductory course in Econometrics. The course is designed to provide the students with sufficient knowledge of statistics and econometrics necessary to understand and be able to evaluate and interpret econometrics researches that use basic linear regression methods. The course begins with a link between statistics and linear regression model and its assumptions. Violations of assumptions and their consequences in estimation process are further examined. 

Presentation of the basic concepts and tools used by businesses and investors in financial decision making. The course consists of lectures and problems related to Financial institutions, markets and debt instruments issued by the government of Cyprus, loanable funds theory, determinants of interest rates, yield curves, spot and forward rates, Greek and Cypriot financial crisis, time value of money with applications, private and business loan financing, types and pricing of bonds, evaluation and pricing of stocks, measurement of investment risk, Capital Asset Pricing Model, capital budgeting and cash-flow computation.

The purpose of the course is to study operational research techniques and methodologies aimed at their application for making optimal managerial decisions. Emphasis is placed on problem-solving and the study of models in the fields of finance, management science, economics, and shipping.
Assignments and exercises with software will be carried out during lecture and tutorial periods. Some of these topics will be studied and presented during the course.
Upon completion of the course, students will be able to identify, use, and analyze the appropriate techniques needed to answer various questions in their areas of specialization. The course is specifically tailored for students who are interested in enriching and deepening their knowledge in decision-making within an operational environment.

This course will familiarize you with the area of data visualization. Students will acquire fundamental knowledge about the visualization of data and models. The primary objective is to understand how to transform data into visual representations for the purpose of describing and investigating data, examining hypotheses and correlations, and presenting evidence. Special emphasis will be placed on visualizing data for policy-makers. Students will gain expertise in visualizing diverse data types and formats by employing industry-standard, open-source software. The aim of the course is to comprehend and utilize the principles of data visualization effectively, to enhance capabilities in collecting and managing data for the purpose of visualization, to apply data visualization techniques to analyze pertinent data sets, to gain knowledge and expertise in assessing visualizations quantitatively and qualitatively. Furthermore to further advance skills in using the ggplot2 package for R and other related packages for data visualization.

The course is an introduction to the workings of the international economic system and the economic forces that govern contemporary economic and financial relations between nations. The course consists of two major components. The first component examines international trade, that is the exchange of goods and services between nations. This part of the course does not examine financial exchanges between nations, a topic that is covered in the second part of the course. The first part of the course presents a general overview of international commercial exchanges and an introduction to economic theories that purport to explain these. This part emphasizes the costs and benefits to a nation from participating in international markets. Moreover, it presents a general introduction to protectionism and examines the different types of barriers to trade that nations impose on the flow of international trade and the reasons for the imposition of these barriers. The second part of the course is an introduction to international finance and the role of money and different currencies in financial exchanges between nations. It presents an overview of international financial transactions and introduces a nation’s balance of payments. This is followed by an examination of the foreign exchange market and international parity conditions in the foreign exchange market. Subsequently the course examines the basic theories of the balance of payments and the determination of exchange rates.Throughout the course emphasis is given to the applied dimensions of international trade and finance and the course uses examples from different economies with special mention of the external trade to the European Union and the role of the euro in international financial transactions.

The purpose of this course is to understand how different economic agents such as households, firms and governments make decisions and how those interact together to determine prices and quantities in an economy. The course starts by introducing consumption given preferences and other factors which gives rise to the demand curve both with and without uncertainty. Then the course moves to how firms choose prices and quantities under different market regimes such as perfect competition, monopoly, oligopoly etc. Finally, the course makes an introduction to game theory and Nash equilibrium.  

The course’s purpose is to teach students to be able to answer macroeconomic questions using simple theoretical models. It presents how theoretical models are constructed and the way they are validated using empirical evidence. Initially the course investigates the long run period and specifically how economic growth and inflation are generated in the long run. Then it moves to the short run and explains why the economy may deviate from its long run trend creating unemployment and/or inflation. Last, the course refers to Central banks and how monetary policy affects the short-term equilibrium using its tools of monetary policy. 

The course offers an introduction to financial econometrics for second-cycle studies. It covers the main parts of the spectrum of quantitative financial economics, discusses important results in the empirical finance literature, and provides a comprehensive knowledge to do empirical work in financial practice. 

Multivariate statistical models and methods are essential for analysing complex-structured and possibly high-dimensional data from any areas of science and industry, ranging from biology and medicine, and genetics to finance and sociology. Multivariate statistics also provides the foundation of many machine and statistical learning algorithms.  The aim of the course is to familiarise students with the methodology of multivariate statistics and statistical learning for students specializing in data science, as well as with their practical implementation and application using the R statistical programming language. The course includes the presentation and analysis of research work.

The aim of the course is to provide students with the necessary knowledge to be able to design databases and database systems and to implement databases using SQL language.

The aim of a course on text and data mining is to teach students how to extract useful information from large datasets of unstructured text data. This involves learning how to preprocess text data, represent it in a way that can be analyzed by machine learning algorithms, and apply various techniques such as classification, clustering, and association rule mining to extract insights from the data. The course may also cover topics such as sentiment analysis, topic modeling, web scraping, and social media mining.

This course helps to explore the theory and practice of financial risk management in a variety of common settings, including business, financial markets, the casino, sports betting.
It is also useful for the competitive world of global finance, in fields such as asset management, hedge funds, investment analysis or risk management.

Business economics is a course that applies microeconomic principles to the study of business decisions and strategy. The course will cover topics such as market structures, pricing strategies, production and cost analysis, and market demand. It will also explore the role of government policies on businesses, as well as international trade and globalization. The course will use a combination of theoretical models and real-world case studies to understand these issues.

The aim of the course "Public and Welfare Economics" is to understand the role of the state in the economy and how government intervention in markets affects the efficiency of resource allocation and the equality of income distribution.Upon successful completion of the course, students will have proven knowledge and understanding of all the issues that make up public finance and welfare economics. They will be able to explain why government intervention is needed, how it affects the behavior of the private sector, and what the effects of that intervention are on economic well-being. In addition, by using the existing databases related to public finances and in combination with the tools of Statistics and Econometrics they will be able to provide sufficient objective documentation of the issues they are asked to analyze.

Statistical machine learning is an increasingly important approach to extracting valuable information from data. In particular, and when used appropriately, it allows for a data-driven approach to solving various problems that cannot be solved from first principles alone. The course is designed to develop theoretically and practically a selection of fundamental machine learning problems and commonly used solutions.

The course examines various issues faced by multinational corporations and international investors from their interaction with international money markets. The different problems and challenges faced by participants in international money markets are analyzed, as well as various theories that govern transactions between participants. The emphasis of the course is on the application of the theories with special mention and examples from the European Union and the role of the euro in international financial transactions. 
The course begins with a short overview of the basic concepts of the balance of payments and the foreign exchange market. The course then examines international parity condition in money markets. This is followed by an introduction to the tools available to market participants to hedge foreign exchange risk. 
The second part to the course analyses the nature of  the exposure faced by corporations in their operations within international money markets. The cost and availability of capital in international markets is the next topic. The course examines the means through which corporations can fund their operations, that is through equity capital or debt.  To conclude, the course examines the international management of portfolios by investors. 

The course aims to help the student to understand the theory and practice of modern banking financial institutions. The student will be able to understand the special nature of banking operations, the structure of the banking industry, diversification of banking, insurance and banking, international banking and multinational banks. Specific topics covered include the regulation of the banking sector, the banking sector in emerging markets, banking reforms, the banking sector in Cyprus. Moreover, the course refers to central banking monetary policy and how it affects banks, interest rates and the economy.

The "Introduction to Marketing" course examines the basic principles governing contemporary marketing thought and practice.
The purpose of the course is to provide the introductory knowledge around the basic philosophy, theories and concepts of marketing in order to help students to develop skills and critical thinking necessary to diagnose, analyze and solve marketing problems.
In addition, the course aims to familiarize students with Marketing processes, methods and techniques such as Strategic Business Planning, Marketing Planning and Process, Market Research and Consumer Behavior, Segmentation, Targeting, Positioning, Product Strategies, Pricing, Distribution and Promotion-communication.

The main objective of the Internship is to give students the opportunity to understand the problems and trends in the field of data science by placing them in a work environment with real working conditions. Students can assess whether the environment in question is related to their academic studies and prepare appropriately for their successful integration into the labor market, after completing their studies. By extension, the Department benefits from the combination of strengthened relationships with domestic industry and with other organizations/bodies.

Labour economics is a course that examines the interactions between workers, employers, and labour markets. This course will cover topics such as labour demand and supply, wage determination, discrimination, labour unions, and unemployment. It will also explore the role of government policies in labour markets, such as minimum wage laws and unemployment insurance. The course will use a combination of theoretical models and empirical evidence to understand these issues.

The Economics of Risk and Uncertainty is a course that explores how individuals and firms make decisions in the face of uncertainty. The course will cover topics such as decision making under uncertainty, risk management, behavioural economics and decision making, the role of information in decision making, and the economics of information. The course Introduces the expected utility model for this task. The course will use a combination of theoretical models and empirical evidence to understand these issues and develop tools to analyse and manage risk.

Economic Growth and Development is a course that explores the economic, political, and social factors that influence the growth and development of countries around the world. The course will cover various theories and models of economic growth and development, as well as case studies of different countries and their experiences with economic growth.

This course aims at providing students with an introduction to the economic approach to politics, also known as positive political theory or rational choice theory.  

In this course the student is required to prepare a Thesis under the supervision of a Faculty member of the Department. The student is expected to complete an independent research on a (real-world) business topic using their knowledge and skill-set (with the approval of his / her academic supervisor). This module aims:

· To provide students with the necessary training to undertake advanced-level research in their field.
 · To provide students with an advanced understanding of the relevance and importance of alternative epistemological positions in the social sciences and the nature of both qualitative and quantitative approaches to research;
· To develop students’ understanding at an advanced research, by examining the study skills necessary to manage and undertake a research project;
· To provide students with opportunities to be familiar with the frontier empirical and theoretical research;
· To provide students with the opportunity to conduct an in-depth investigation at an advanced level of an issue which is applicable in the real world/business environment.