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Programme:

Business Analytics and Artificial Intelligence (2026/2027)

Study Cycle: First Cycle (Undergraduate)
Faculty: Business and Economics
Programme Code: BAAI-240
Academic year: 2023 / 2024
Title: Bachelor of Economics in Business Analytics and Artificial Intelligence
ECTS: 240 (4 years)
Decision:

The Business Analytics and Artificial Intelligence study program is designed to respond to the increasing demand for professionals who can combine business knowledge with advanced analytical and artificial intelligence skills. Modern organizations rely on data-driven decision-making, predictive analytics, and intelligent systems to remain competitive in a rapidly evolving digital economy. The program integrates core business disciplines with modern analytical tools, programming skills, and artificial intelligence applications. Students develop competencies in data analysis, machine learning, database systems, and digital business strategy, while maintaining a strong foundation in economics, finance, management, and marketing. A particular emphasis is placed on the practical application of analytics and AI in business environments, including supply chain management, financial analysis, digital transformation, and strategic decision-making. Students gain experience with programming languages such as Python and analytical tools used for business intelligence, data mining, and machine learning. The program also reflects the growing importance of ethical governance of artificial intelligence, digital transformation, and the use of intelligent systems in organizations. Through courses such as AI Regulation, Governance and Ethics, Intelligent Systems and Agentic AI, and Machine Learning, students acquire the knowledge required to responsibly develop and implement AI-driven solutions.

The study program prepares graduates for careers such as:

  • Business Analyst
  • Data Analyst
  • AI Business Specialist
  • Business Intelligence Analyst
  • Digital Transformation Consultant
  • Data-driven Strategy Analyst

Graduates may also continue their studies in postgraduate programs in business analytics, artificial intelligence, digital business, or data science. The program also addresses ethical and regulatory aspects of artificial intelligence. Students gain knowledge about responsible use of AI, algorithmic transparency, and governance frameworks that are increasingly required in modern organizations and in European regulatory frameworks.

Graduates of this program are prepared for careers in fields that integrate data analysis with business decision-making, including roles such as business analyst, data analyst, AI business specialist, and digital transformation consultant. They possess competencies in the use of analytical tools, machine learning techniques, and programming languages for data analysis and for supporting organizational strategies, and can be employed across various sectors such as finance, marketing, information technology, and consulting services..

Knowledge and understanding

Graduates of the Business Analytics and Artificial Intelligence study program acquire:

Core Business Knowledge

A solid understanding of fundamental business concepts including management, finance, marketing, operations, and strategic decision-making processes.

Quantitative and Analytical Knowledge

Knowledge of statistical methods, mathematical modeling, and data analysis techniques used for solving complex business problems.

Data Management and Technologies

Understanding of data structures, databases, data warehousing, and modern data processing platforms used for storing and managing large datasets.

Business Intelligence and Analytical Tools

Knowledge of analytical software and programming environments used in business analytics such as Excel, SQL, Python, R, Tableau, and Power BI for data analysis, visualization, and reporting.

Artificial Intelligence and Machine Learning

Understanding of fundamental concepts of artificial intelligence, machine learning algorithms, and predictive analytics methods applied in business contexts.

Data Engineering and Cloud Technologies

Knowledge of data engineering principles and cloud computing technologies used for large-scale data processing and analytical systems.

Data-Driven Problem Solving

Understanding of how analytical insights can be integrated into business decision-making to improve operational efficiency, strategic planning, and organizational performance.

Ethics and Data Governance

Awareness of ethical considerations, data privacy principles, and legal regulations governing the responsible use of data and artificial intelligence technologies.

Emerging Digital Technologies

Knowledge of current technological trends including artificial intelligence, big data analytics, and cloud computing and their implications for modern organizations.

Applying knowledge and understanding

Graduates of the Business Analytics and Artificial Intelligence study program will be able to:

Apply Analytical Methods to Real-World Problems

Use statistical, quantitative, and computational methods to analyze business data and generate actionable insights for organizational decision-making.

Utilize Business Intelligence Tools

Apply analytical tools and programming environments such as Excel, SQL, Python, R, and data visualization platforms (e.g., Tableau and Power BI) to analyze data and support managerial decision-making.

Develop Data-Driven Solutions

Design and implement analytical models and predictive algorithms to improve operational efficiency, marketing strategies, financial performance, and customer experience.

Conduct Independent Data Analysis

Identify relevant data sources, collect and prepare datasets, and perform analytical evaluations to support business decisions and strategic initiatives.

Integrate Analytics into Business Functions

Translate analytical findings into business insights that support decision-making in areas such as supply chain management, finance, marketing, and human resource management.

Support Data-Driven Decision-Making

Apply analytical results and data insights to support strategic and operational decisions in dynamic business environments.

Develop Analytical Reports and Dashboards

Design dashboards, visualizations, and analytical reports that communicate complex data insights clearly to different stakeholders.

Apply Ethical and Legal Principles in Data Use

Use data responsibly by respecting principles of data governance, ethical data usage, and relevant legal and regulatory frameworks.

Entrepreneurial and Innovation Skills

Apply analytical and technological knowledge to identify new business opportunities and support the development of data-driven entrepreneurial initiatives.

Making judgement

Graduates of the Business Analytics and Artificial Intelligence study program will be able to:

Critically Evaluate Data and Analytical Results

Assess the quality, reliability, and validity of data sources and analytical outputs, identifying potential biases, limitations, and risks in analyses.

Interpret Analytical Findings in Business Contexts

Relate quantitative results to business objectives, market dynamics, and organizational strategies in order to support informed decision-making.

Select Appropriate Analytical Methods and Tools

Evaluate and choose suitable analytical techniques, models, and software tools depending on the nature of the business problem and the characteristics of the data.

Integrate Analytical Insights with Business Considerations

Balance quantitative evidence with qualitative factors, ethical implications, and organizational constraints when evaluating alternative solutions.

Identify Opportunities and Risks Using Data

Analyze business environments and datasets to detect strategic opportunities, potential risks, and emerging trends relevant to organizational performance.

Develop Evidence-Based Recommendations

Formulate well-supported recommendations and strategic insights based on analytical evidence and sound reasoning.

Demonstrate Independent and Critical Thinking

Approach complex business and analytical challenges independently, applying critical thinking and analytical rigor in problem-solving.

Communication skills

Graduates of the Business Analytics and Artificial Intelligence study program will be able to:

Present Analytical Results Clearly

Communicate complex analytical findings and technical information in a clear, concise, and structured manner to both technical and non-technical audiences.

Develop Effective Data Visualizations

Design charts, dashboards, and analytical reports that effectively communicate insights and support data-driven decision-making.

Prepare Professional Analytical Reports

Produce well-structured written reports documenting analytical methods, results, and business recommendations.

Adapt Communication to Different Stakeholders

Adjust communication style and content to suit different audiences, including managers, executives, clients, and technical specialists.

Collaborate in Multidisciplinary Teams

Work effectively in cross-functional teams, sharing analytical insights, contributing to discussions, and integrating feedback from diverse perspectives.

Translate Technical Concepts into Business Language

Explain analytical models, statistical results, and technological concepts in a clear and understandable way that supports managerial decision-making.

Advocate Data-Driven Decision Making

Present and defend analytical conclusions and recommendations using evidence-based reasoning.

Learning skills

Graduates of the Business Analytics and Artificial Intelligence study program will be able to:

Engage in Lifelong Learning

Continuously update their knowledge and skills in response to evolving technologies, analytical tools, and business practices in the field of data analytics and artificial intelligence.

Independently Acquire New Knowledge

Identify personal learning needs and independently access relevant resources such as academic publications, professional training, and digital learning platforms.

Adapt to Emerging Technologies

Learn and apply new programming languages, analytical methods, and technological tools relevant to business analytics and artificial intelligence.

Reflect on Personal Learning and Development

Evaluate their own learning processes and outcomes in order to improve analytical competencies and professional performance.

Research and Evaluate Information

Identify, critically assess, and integrate information from diverse sources to support analytical work and decision-making.

Develop Problem-Solving Strategies

Apply analytical thinking and learning strategies to address unfamiliar problems and develop innovative data-driven solutions.

Participate in Professional Development

Engage in professional training, workshops, certifications, and other learning opportunities to enhance expertise in business analytics and related digital technologies.

Semester 1

  • [C2640] [6 ECTS] Principles of Management
    The subject aims to acquaint students with the essence of management and create a base which will be supplemented by other managerial and organizational subjects that students will listen to during their study. This subject has several main purposes, including: Students understand and clarify key management concepts and theories. - To initiate critical thinking in the classroom. - To enable students to use the information gained to give assessments and construct arguments. - To develop students' communication skills. - To inform students about the management process and the tasks of the manager. - To inform students about the planning process. - To inform students with decision-making processes and models. - To acquaint students with the organization, including the division of labor and the breadth and depth of management. - Students should be able to apply in practice knowledge on individual-organizational relationships and various elements related to organizational behavior, including personality, behaviors and perceptions. - Students gain knowledge on motivation and motivation theories.
  • [C2638] [6 ECTS] Fundamentals of Economics and Business
    Objectives:  To understand the fundamental concepts of economics and business.  To develop the ability to analyze the relationship between economic factors and business decisions.  To enable students to use basic economic and business terminology.  To foster critical thinking and the ability to connect theory with real market practices. Upon completion of the course, the student will be able to:  Explain the fundamental concepts of economics and business.  Identify the factors influencing the functioning of markets and enterprises.  Apply basic knowledge to analyze simple economic and business situations.  Effectively communicate economic and business ideas.  
  • [C2639] [6 ECTS] Business Mathematics
    Course Objectives: - Students will be encouraged to actively participate in discussions and solve various tasks and problems related to mathematics. - Students will become familiar with the basic concepts of linear algebra and apply their knowledge through linear models in the fields of Energy, Economy and Environment. - Students will gain a solid understanding of arithmetic and geometric progressions and apply them to solve various problems in Energy, Economy and Environment. - Students will acquire sufficient knowledge in financial mathematics and apply it to the fields of Energy, Economy and Environment.
  • [C2121] [3 ECTS] Business, Government and Society
    The subject aims to create, develop, and advance students’ knowledge in the field of relations between business, government institutions, and society. Through this subject, students will acquire basic and practical knowledge regarding: • the importance of BGS for future managers and professionals; • corporations and their stakeholders; • public affairs management and stakeholder relations; • business operations in a globalized world; • organizational ethics and responsibility; • the business–government relationship; • the role of technology and its impact on social and economic relations; • contemporary challenges in the interaction between economic development, governance, and public interest.
  • [C2861] [3 ECTS] Business Communication
    The aim of this course is to introduce students to the fundamental principles of business communication and to develop their ability to communicate effectively in professional and organizational environments. The course focuses on improving verbal, non-verbal, written, and digital communication skills that are essential for collaboration, negotiation, and professional interaction in modern business organizations. After completing this course students will be able to: 1. Understand the principles and importance of business communication in organizations. 2. Apply verbal and non-verbal communication techniques in professional contexts. 3. Prepare clear and effective written business documents such as emails, reports, and memos. 4. Demonstrate effective communication skills in meetings, presentations, and negotiations. 5. Use digital communication tools appropriately in professional environments. 6. Communicate ideas clearly and professionally in multicultural and organizational settings.
  • [3 ECTS] English Language
    • [E2532] English Language 1
    • [E2533] English Language 2
    • [E2534] English Language 3
    • [E2535] English Language 4
    • [E2536] English Language 5
    • [BEEN-01] Business English 1
    • [BEEN-02] Business English 2
  • [3 ECTS] Albanian/Macedonian Language
    • [BAM1010] Albanian Language for Beginners 1
    • [BAM2010] Albanian Language for Beginners 2
    • [BS018] Macedonian Language for Beginners 1
    • [BS152] Macedonian Language for Beginners 2
    • [MLIL-01] Macedonian Language Intermediate Level 1
    • [MLIL-02] Macedonian Language Intermediate Level 2
    • [MAPP1010] Macedonian Language for Professional Purposes 1

Semester 2

  • [CBE-302] [6 ECTS] Business Calculus
    The Calculus course is designed to provide students with an understanding of the fundamental concepts and their practical applications in the fields of business, economics, and finance. Students should be able to apply calculus techniques to solve real-world problems involving optimization, marginal analysis, and economic modeling. Learning Outcomes: - Students will understand the main concepts of calculus including limits, derivatives, and integrals, as well as continuity, differentiability, and optimization. - Will be able to apply mathematical techniques to economic models to analyze cost functions, revenue models, and profit maximization. Understand the relationships between marginal cost, marginal revenue, and marginal profit. - Solve optimization problems and interpret mathematical results in the context of business and economic decisions.
  • [CBE-203] [6 ECTS] Microeconomics
    The subject aims to introduce students to the principles and concepts of Microeconomics, which will introducs and enable Business and Economics students with the necessary analytical tools and techniques to analyze and provide solutions to relevant and current issues in the field of Microeconomics. This subject will equip students with theoretical and practical knowledge as follows: 1. Demand and supply analysis and market equilibrium; 2. Elasticity and its application, 3. Cost analysis and their application; 4. Analysis of profit maximization in all types of competition; 5. Full and incomplete competition; and 6. Government and microeconomics.
  • [C2641] [6 ECTS] Principles of Marketing
    This course offers students an overview of marketing functions, with an emphasis on creating value through marketing, market research, consumer behavior, pricing strategies, marketing channels and distribution, and promotion methods. Students will be able to:  understand the role of marketing within society and within the economic system.  learn the vital role of marketing within a firm and the necessary relationships between marketing and other functional areas of business.  consider the various areas of decision-making within marketing and the tools and methods used by marketing managers in making decisions.  learn key marketing principles, terminology, and concepts.  appreciate how the marketing aspect is important in their personal and professional development.
  • [C2120] [6 ECTS] Principles of Accounting
    The aim of the subject is to help students understand the essence of accounting; to learn the basic concepts and principles of accounting. In this regard, the subject aims to provide students with knowledge and understanding of financial statements, their items, basic rules to record accounting data, generally accepted accounting principles, etc.
  • [3 ECTS] Albanian/Macedonian Language
    • [MAPP1020] Macedonian Language for Professional Purposes 2
    • [BAM1010] Albanian Language for Beginners 1
    • [BAM2010] Albanian Language for Beginners 2
    • [BS018] Macedonian Language for Beginners 1
    • [BS152] Macedonian Language for Beginners 2
    • [MLIL-01] Macedonian Language Intermediate Level 1
    • [MLIL-02] Macedonian Language Intermediate Level 2
  • [3 ECTS] English Language
    • [E2532] English Language 1
    • [E2533] English Language 2
    • [E2534] English Language 3
    • [E2535] English Language 4
    • [E2536] English Language 5
    • [BEEN-01] Business English 1
    • [BEEN-02] Business English 2

Semester 3

  • [EBE-410] [6 ECTS] Business Law
    Students should acquire knowledge and skills to: • Understand and interpret the fundamental concepts of business Law, including contracts and legal relationships between commercial entities; • Apply knowledge of civil law and law of legal persons in the commercial context; • Analyze and assess legal relationships and obligations in commercial activities and everyday business; • Solve specific legal problems related to commercial activity and the rule of law in this field.
  • [CBE-402] [6 ECTS] Financial Accounting
    The objective of this course is to provide knowledge and skills regarding the process of recording, summarizing, and reporting business transactions of commercial companies, in accordance with the Law on Accounting in the Republic of North Macedonia and the International Accounting Standards (IAS). Special emphasis is placed on the preparation and interpretation of financial statements, including: the Balance Sheet and the Income Statement, the Tax Balance – Corporate Income Tax and General Revenue Tax, as well as other reports in compliance with the Law on Accounting in the Republic of North Macedonia.  
  • [CBE-303] [6 ECTS] Macroeconomics
    Students will gain knowledge of: - macroeconomic concepts and categories, which are a precondition for the functioning of a national economy that is part of a wider global economic system; - the importance of key macroeconomic indicators such as: gross national product, national income, economic growth, economic cycle, investment and public consumption, inflation, unemployment, money and banks, budget, balance of payments, etc .; - basic instruments of macroeconomic analysis (aggregate supply and demand) and macroeconomic policies (monetary and fiscal policy), etc .; - the efficient functioning of a national economy, comparing it with modern market economies, noting in that direction changes, similarities and opportunities for the future development of the respective economy; - Knowledge in the field of macroeconomics, which will enable easier access to other advanced macroeconomic courses.
  • [C2864] [6 ECTS] Statistics for Business
    Aims of the course: • Understand and apply statistical methods to analyze economic indicators, energy consumption, and environmental parameters. • Use statistics for forecasting and decision-making in various sectors. • Master the use of statistical software such as SPSS, R, Python, and Excel. Learning outcomes: • Students will be able to analyze economic indicators (GDP, unemployment, inflation) and interpret data related to energy and the environment. • Students will apply statistical methods to forecast energy consumption and environmental impact. • Students will produce structured reports and interpretations based on statistical data.
  • [3 ECTS] English Language
    • [E2532] English Language 1
    • [E2533] English Language 2
    • [E2534] English Language 3
    • [E2535] English Language 4
    • [E2536] English Language 5
    • [BEEN-01] Business English 1
    • [BEEN-02] Business English 2
  • [3 ECTS] Elective/Digital Comptenecies
    • [E3073] Digital Competencies
    • [E3076] Digital Media Design
    • [E3077] Introduction to Cybersecurity
    • [E3071] Artificial Intelligence: Tools and Applications
    • [E3072] Spreadsheet Modeling

Semester 4

  • [CBEM-603] [3 ECTS] Organizational Behavior
    The aim of this course is to provide students with fundamental knowledge of organizational behavior, focusing on how individuals and groups behave within organizations. The course examines key concepts such as motivation, leadership, communication, group dynamics, and organizational culture, enabling students to understand and analyze behavior in organizational settings. Learning outcomes: • explain the fundamental concepts and theories of organizational behavior • analyze individual behavior in organizations, including personality, perception, and motivation • understand group dynamics and teamwork in organizational settings • evaluate leadership styles and their impact on organizational performance • analyze communication processes within organizations • understand the influence of organizational culture and organizational structure on employee behavior • apply organizational behavior concepts to real organizational situations
  • [C2130] [3 ECTS] International Business
    The course aims to provide students with a solid understanding of the global business environment and the complex forces that drive globalization, including technological change, trade liberalization, and evolving consumer preferences. A central focus is placed on exploring the various strategies that firms employ when entering international markets, such as exporting, joint ventures, franchising, and foreign direct investment, while highlighting the advantages and limitations of each approach. In addition, students will critically analyze the political, economic, and cultural risks and opportunities that shape international business activities, enabling them to recognize both the challenges and benefits of cross-border operations. The course further seeks to equip students with the essential skills needed to make informed decisions related to international trade, investment, and finance, by integrating theoretical knowledge with practical case studies. Finally, special emphasis is given to understanding the broader impact of international business on local economies and cultures, encouraging students to evaluate how global business practices influence development, employment, sustainability, and cultural exchange in different regions of the world.
  • [C2124] [6 ECTS] Business Information Systems
    Aims: • Understand core concepts of business information systems. • Explain the role of IS in strategy, management, and decision-making. • Analyze issues of ethics, privacy, and information security. • Develop practical skills in using digital systems for business. Learning Outcomes: Students will be able to: • Define IS and explain their key functions. • Identify opportunities for competitive advantage through IS. • Apply knowledge of databases, networks, and business applications. Evaluate the impact of IS on society, organizations, and individuals.  
  • [CBE-401] [6 ECTS] Operations Management
    Students get acquainted with the complex issues of production management understood as a process of planning and organization of production, but also as control of the functioning of production as a system, to achieve production goals in the most effective and efficient ways. Within this framework, special attention is paid to the following aspects of production management: production as a system, production system planning, product-product design, product-product quality, product production program, production location, capacity of production, production equipment, factory buildings, factory space planning, production processes, timely production planning and monitoring, inventory control, internal storage and transport system, equipment and building maintenance and production assurance energy, cost control and organizational structure of production.
  • [CBM-502] [6 ECTS] Corporate Finance
    The objectives of this course are to equip students with advanced knowledge and to broaden their existing competencies toward understanding contemporary theoretical and practical aspects of financial management and corporate finance. Special emphasis is placed on analyzing the condition and performance of businesses/corporations through financial statements and other relevant sources, as well as on the application of modern techniques of investment decision-making.
  • [3 ECTS] English Language
    • [E2532] English Language 1
    • [E2533] English Language 2
    • [E2534] English Language 3
    • [E2535] English Language 4
    • [E2536] English Language 5
    • [BEEN-01] Business English 1
    • [BEEN-02] Business English 2
  • [3 ECTS] Elective/Digital Comptenecies
    • [E3073] Digital Competencies
    • [E3076] Digital Media Design
    • [E3077] Introduction to Cybersecurity
    • [E3071] Artificial Intelligence: Tools and Applications
    • [E3072] Spreadsheet Modeling

Semester 5

  • [ECS-609] [6 ECTS] Introduction to Artificial Intelligence
    The aim of this course is to introduce the fundamental concepts and methods of artificial intelligence, including intelligent agents, knowledge representation, search techniques, logical and probabilistic reasoning, and basic machine learning approaches. The course provides an overview of how artificial intelligence systems support problem solving and decision-making in modern digital and business environments. After completing this course, students will be able to: 1. Explain the fundamental concepts and terminology of artificial intelligence. 2. Describe the role of intelligent agents, knowledge representation, and search algorithms in AI systems. 3. Understand basic methods of logical and probabilistic reasoning used in artificial intelligence. 4. Identify key approaches to machine learning and neural networks. 5. Recognize the applications of artificial intelligence in modern digital and business environments. 6. Analyze the potential benefits and limitations of AI technologies.
  • [C2306] [6 ECTS] Programming in Python
    The aim of the course is to introduce students to the fundamentals of programming using the Python programming language. The course develops basic programming skills including data types, control structures, algorithm design, functions, and object-oriented programming. Students will learn how to use Python to solve practical problems and perform basic data analysis tasks relevant to business analytics and artificial intelligence applications. After completing the course, students will be able to: • Understand the basic principles of programming and algorithmic thinking. • Write Python programs using variables, control structures, functions, and modules. • Apply object-oriented programming concepts in Python. • Use Python libraries for basic data manipulation and analysis. • Develop simple applications and scripts for solving business and analytical problems. Prepare datasets and perform preliminary data analysis for further analytics and AI courses.
  • [C2865] [3 ECTS] AI Regulation, Governance and Ethics
    Course aims: • Introduce students to the regulatory, governance, and ethical dimensions of artificial intelligence in modern organizations and society. • Provide knowledge about international and regional regulatory frameworks governing artificial intelligence technologies. • Develop understanding of responsible AI principles including fairness, transparency, accountability, and privacy. • Analyze ethical challenges related to algorithmic decision-making, data governance, and automated systems. • Equip students with analytical tools to evaluate the societal and business implications of AI adoption. • Encourage critical thinking regarding responsible innovation and sustainable digital transformation. After completing the course, students will be able to: • Define and explain key concepts related to artificial intelligence governance and regulation. • Identify the main ethical challenges related to the deployment of AI systems in business and society. • Analyze international regulatory frameworks including the European Union AI Act and global governance initiatives. • Evaluate risks related to algorithmic bias, discrimination, transparency, and accountability. • Apply principles of responsible AI in business decision-making and organizational governance. • Assess ethical implications of AI applications in finance, marketing, public administration, and digital platforms. • Develop policy or governance recommendations for responsible AI adoption in organizations. • Work collaboratively to analyze case studies related to AI ethics and regulation.
  • [C2126] [3 ECTS] Supply Chain Management
    Aims: Understand fundamental concepts of supply chain management. Develop skills for planning, organizing, and managing logistics processes. Enable students to use strategies and tools for optimizing supply and distribution. Learning Outcomes: Explain concepts and models of supply chain management. Analyze the role of logistics in organizational performance. Apply methods for managing resources, inventories, and transportation. Propose strategies to improve supply chain efficiency.
  • [6 ECTS] Elective from other unites
    • [CPA-201] Public Leadership and Organizational Development
    • [E2739] Ethics in Public Institutions
    • [ECS3060] IT Professional Ethics
    • [CCS-102] Internet Technologies
    • [E2698] Control of Nosocomial infections
    • [C2527] Basics of Design Studio
    • [E2842] International law on human rights
    • [E2996] New Reproductive Technologies and Law
    • [EPRNM-02] Public Relations and New Media
    • [EFE-129] Albanian Language and Writing Culture
    • [EFB-03] Personal Finances
    • [EBE-408] Project Management
    • [EBE-403] Business Plan
    • [E2997] Common Sense Economics
    • [EDOL-03] Digital and Online Literacy
    • [E2531] English Literature and Film
  • [6 ECTS] Business Elective Course
    • [E3079] Business Ethics and Corporate Responsibility
    • [E3080] Business Consulting and Problem Solving
    • [CBEE-803] Labor Market
    • [EBEE-605] Environmental Economics
    • [EBA034] Local Economic Development
    • [C2132] E-Commerce
    • [E2750] Data Analysis with Python/R
    • [EBEF-801] Financial Modeling
    • [E3085] Entrepreneurial Finance
    • [E3086] Negotiation and Conflict Management
    • [E3084] Sales Management and Customer Relationships
    • [CEM-503] Human Resource Management

Semester 6

  • [C2128] [6 ECTS] Strategy and Organization
    The aim of this course is to provide students with knowledge of the concepts and processes of strategic management and organizational design. The course focuses on analyzing the internal and external environments of organizations, formulating and implementing competitive strategies, and understanding the role of organizational structure in strategy implementation. Learning outcomes: • understand key concepts of strategic management • analyze the internal and external environment of organizations • identify and evaluate competitive strategies • understand the relationship between strategy and organizational structure • develop analytical skills for strategic decision-making
  • [CCS-403] [6 ECTS] Databases
    This course covers an introduction to database design and use of databases, with a short introduction to the internals of relational database management systems. It includes extensive coverage of the relational model, relational algebra, and SQL. The course also features database design and relational design principles based on dependencies and normal forms. A student who successfully will complete this course will be able to use the models and concepts of designing databases. He / She will be able to use database, to design a simple and specific database based on the relational database model, to use MS SQL Server database management system (DBMS), SQL language and implementation of queries. After completing this course, students will be able to: 1. Explain the fundamental concepts of database management systems. 2. Understand the relational data model and principles of database design. 3. Design conceptual database models using E-R diagrams. 4. Apply normalization techniques in database design. 5. Use SQL to create, manipulate, and query databases. 6. Implement and manage simple relational databases in DBMS environments.
  • [ECS-604] [6 ECTS] Data Mining
    The aim of this course is to introduce the fundamental concepts and techniques of data mining and knowledge discovery from large datasets. Students will learn methods for data preprocessing, data warehousing, classification, prediction, clustering, association rule mining, and data visualization. The course also focuses on building and evaluating analytical models and interpreting results. In the practical part of the course, students implement data mining algorithms and models using Python and modern data analysis tools. After completing this course, students will be able to: 1. Understand the process of knowledge discovery in databases (KDD). 2. Apply data preprocessing and transformation techniques. 3. Use classification, prediction, and clustering methods. 4. Apply algorithms for association rule mining. 5. Build and evaluate analytical models using modern data analysis tools. 6. Interpret and visualize data mining results.
  • [6 ECTS] Elective from other unites
    • [CPA-201] Public Leadership and Organizational Development
    • [E2739] Ethics in Public Institutions
    • [ECS3060] IT Professional Ethics
    • [CCS-102] Internet Technologies
    • [E2698] Control of Nosocomial infections
    • [C2527] Basics of Design Studio
    • [E2842] International law on human rights
    • [E2996] New Reproductive Technologies and Law
    • [EPRNM-02] Public Relations and New Media
    • [EFE-129] Albanian Language and Writing Culture
    • [EFB-03] Personal Finances
    • [EBE-408] Project Management
    • [EBE-403] Business Plan
    • [E2997] Common Sense Economics
    • [EDOL-03] Digital and Online Literacy
    • [E2531] English Literature and Film
  • [6 ECTS] Business Elective Course
    • [E3079] Business Ethics and Corporate Responsibility
    • [E3080] Business Consulting and Problem Solving
    • [CBEE-803] Labor Market
    • [EBEE-605] Environmental Economics
    • [EBA034] Local Economic Development
    • [C2132] E-Commerce
    • [E2750] Data Analysis with Python/R
    • [EBEF-801] Financial Modeling
    • [E3085] Entrepreneurial Finance
    • [E3086] Negotiation and Conflict Management
    • [E3084] Sales Management and Customer Relationships
    • [CEM-503] Human Resource Management

Semester 7

  • [ECS3080] [6 ECTS] Machine Learning
    The aim of this course is to introduce the fundamental concepts, techniques, and algorithms of machine learning. Students will learn how machines can learn patterns from data and use these patterns to make predictions and decisions. The course covers supervised and unsupervised learning methods, model evaluation, and practical implementation of machine learning algorithms. Students will apply machine learning techniques to real-world problems using modern data analysis tools. After completing this course students will be able to: 1. Understand the fundamental concepts of machine learning. 2. Distinguish between supervised and unsupervised learning methods. 3. Implement basic machine learning algorithms. 4. Build and evaluate predictive models. 5. Analyze and interpret machine learning results. 6. Apply machine learning techniques to real-world data problems.
  • [C2872] [6 ECTS] Data Engineering
    The aim of this course is to teach the fundamentals of data modelling, cleaning, transformation and storage. As such students will learn various means to model SQL and NoSQL data, organize them in different data stores, design and manage data pipelines. Students will also learn how to use state of the art tools implemented in premise or cloud. After completing this course, students will be able to: 1. Understand the architecture of modern data systems. 2. Design data models using SQL and NoSQL technologies. 3. Implement ETL processes for data integration and transformation. 4. Design and manage data pipelines. 5. Organize and manage data warehouses. 6. Use modern platforms for data processing and management in cloud or on-premise environments.
  • [E2591] [6 ECTS] Digital Business
    Course objectives: - Understanding the basic definition and hierarchy of knowledge for digital business and understanding the processes related to the operation, marketing techniques and technological issues of digital systems; - Analyzing data on user activity in order to make informed decisions regarding marketing and business management in the organization and product / service development; - Application of basic online positioning (SEO) techniques in creating the marketing image of the organization, as well as the product brand (branding); - Recognizing and understanding the importance of the Internet as an environment for creating social and business processes; - Demonstrate the tendency for active use of the Internet in economic and social activities and the creation of your career.
  • [C2134] [6 ECTS] Business Analytics and Modeling
    The subject focuses on the process of transforming data into information for solving business problems in the real world. The subject has a phased approach to knowledge generation: first, descriptive analytics is taught where visual analysis is used to characterize data; second, it teaches recommendatory analytics that focus on optimal strategies that "should" be undertaken in the future; third, predictive analytics is taught that focuses on the use of algorithms for predicting the future based on historical data. Topics include: data exploration, data preparation, nonlinear optimization, etc.
  • [6 ECTS] Avanced elective courses
    • [E3092] Behavioral Economics
    • [E3081] FinTech and Digital Finance
    • [EACS-19] Data Visualization
    • [EFB-02] Game Theory and Business Strategy
    • [E2589] Business Process Management
    • [E3082] Emerging topics in Business and AI
    • [E2588] Financial Data Analysis
    • [E3083] Applied Accounting
    • [EBEM-504] International Marketing
    • [E2579] Real Estate Finance and Investment Analysis
    • [E3087] Environmental Data Analysis and Carbon Accounting
    • [EBA-075] Аuditing
    • [E3032] Logistics and Automation

Semester 8

  • [CBEE-603] [6 ECTS] Econometrics
    The aim of the course is to equip students with knowledge and skills to apply statistical and mathematical methods in the analysis of economic data. The course develops competencies in constructing and interpreting econometric models, testing hypotheses, and making forecasts. Learning outcomes: Students will understand the theoretical foundations of econometrics and its connection to economics. They will be able to construct and interpret linear regression models. They will gain practical skills in using statistical software for econometric analysis. They will be capable of applying econometric methods for analysis and decision-making in economics and finance.
  • [C2866] [6 ECTS] Intelligent Systems and Agentic AI
    The aim of this course is to introduce students to the fundamental concepts, architectures, and applications of intelligent systems, with particular emphasis on agent-based artificial intelligence and modern agentic AI systems. The course seeks to develop students’ understanding of how intelligent systems perceive environments, process information, make decisions, and act autonomously. Through the study of theoretical models and practical applications, students will gain the ability to analyze and evaluate the use of intelligent systems and autonomous agents in various domains such as business, technology, data analytics, and decision-support systems. After completing this course students will be able to: 1. Explain the fundamental concepts of intelligent systems and agent architectures. 2. Analyze knowledge representation and reasoning mechanisms in intelligent systems. 3. Evaluate the role of machine learning in intelligent systems. 4. Design basic intelligent agents and multi-agent systems. 5. Analyze the concept of agentic AI and the use of large language models in autonomous systems. 6. Evaluate ethical and societal implications of intelligent systems.
  • [C2322] [6 ECTS] Cloud Infrastructure and Technologies
    This course introduces to students the foundational knowledge required for understanding cloud computing from different perspectives, both technological and the bussines one. Students will learn about the various cloud service models (IaaS, PaaS, SaaS), deployment models (Public, Private, Hybrid) and the key components of a cloud infrastructure (VMs, Networking, Storage - File, Block, Object, CDN). The course also cover emergent cloud trends and practices including - Hybrid Multicloud, Microservices, Serverless, DevOps, Cloud Native and so on. Finally some other important topics such as cloud security, monitoring, and different job roles in the cloud industry are explained. After completing this course, students will be able to: 1. Understand the architecture and concepts of cloud computing. 2. Distinguish between cloud service models (IaaS, PaaS, SaaS). 3. Analyze different cloud deployment models (public, private, hybrid). 4. Configure and manage key cloud infrastructure components. 5. Understand modern cloud technologies such as containers, serverless computing, and cloud-native architectures. 6. Evaluate security and management challenges in cloud environments.
  • [C2867] [6 ECTS] Capstone Project
    The Capstone Project in the study program Business Analytics and Artificial Intelligence represents a final project in which the student is expected to demonstrate the knowledge and skills acquired during their studies by addressing a real or simulated problem in the field of business analytics and/or artificial intelligence. The student is required to identify a research or applied topic, clearly define the problem, conduct a relevant literature review, collect and analyze data using statistical and analytical methods as well as artificial intelligence tools (such as Python, SQL, or BI platforms), and interpret the results in a business context. The Capstone Project should demonstrate critical thinking, problem-solving abilities, and data-driven decision-making, and conclude with clear and well-justified recommendations. In addition, the student must adhere to ethical principles in data use and to academic standards of writing and presenting the thesis.
  • [6 ECTS] Avanced elective courses
    • [E3092] Behavioral Economics
    • [E3081] FinTech and Digital Finance
    • [EACS-19] Data Visualization
    • [EFB-02] Game Theory and Business Strategy
    • [E2589] Business Process Management
    • [E3082] Emerging topics in Business and AI
    • [E2588] Financial Data Analysis
    • [E3083] Applied Accounting
    • [EBEM-504] International Marketing
    • [E2579] Real Estate Finance and Investment Analysis
    • [E3087] Environmental Data Analysis and Carbon Accounting
    • [EBA-075] Аuditing
    • [E3032] Logistics and Automation
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