EDUBA

Duration of the course (lectures): 12 weeks

Lecturer: Prof. Dr. Christiane Naumann

Language: English

ECTS: 5

Type of examination: Written examination

Learning outcomes: The students should be able to describe simple problems within the scope of the performance and management process of companies using technical language. They should be able to get an overview of various functional areas of business administration and be able to understand basic structures and concepts of these areas.

Course content: 

• History and methods of Business Administration
• Companies and the environment
• Constitutive decisions
• Concepts of Strategic Management
• Concepts of Management
• Concepts of Leadership
• Concepts of Motivation
• Service and production
• Concepts of personal management
• Concepts of marketing
• Concepts of organizational design

Timetable: Wednesdays (8.10.2025-14.01.2026): 9:00-10:30; 15:00-16:30 (Kyiv time)

Duration of the course (lectures): 12 weeks

Lecturer: Prof. Dr. Christiane Naumann

Language: English

ECTS: 5

Type of examination: Term paper

Learning outcomes: In addition to the theoretical discussion of essential soft skills, a practical implementation of the idea behind intercultural competence takes place simply and playfully. In this context, students will get an idea of how to interact successfully and appropriately with individuals and groups from other cultures - in the narrower sense, students gain their ability to deal with people of different cultural orientations in a mutually satisfactory manner.

Course content: 

• Analysis of cultural origin
• Identity, Stereotypes, and Culture Shock
• Communication and perception
• Identification of cultures and how they differ from each other
• Principles, theories, and models of cultural studies and dimensions (Hofstede, Trompenaars, GLOBE-study, etc.)
• Gender and diversity competence
• Concepts and dimensions of corporate culture
• Globalization and ethics
• East vs. West – a matter of culture

Timetable: Tuesdays (7.10.2025-13.01.2026): 12:30-14:00; 18:30-20:00 (Kyiv time)

Duration of the course (lectures): 12 weeks

Lecturer: Dr. Mahammad Abujarad

Language: English

ECTS: 5

Type of examination: Written examination

Learning outcomes: Strengthen the ability to apply mathematical and statistical methods to business and economic problems.

Course content: 

Fundamentals of Financial Mathematics

• Mathematical basics
• Depreciation
• Introduction to the calculation of interest and compound interest
• Introduction to the calculation of annuities
• Introduction to the amortization calculation
• Calculation of effective interest rates

Basics of calculus

• Mathematical function concept and economic functions
• Differential quotient and differential
• Economic applications of differential calculus
• Integral calculus and economic applications (consumer and producer surplus)
• Taylor's theorem for approximating differentiable functions

Basics of linear algebra

• Introduction to the calculus of matrices
• Applications of the calculus of matrices
• Linear systems of equations and their applications

Timetable: Tuesdays (7.10.2025-13.01.2026): 16:45-18:15; 18:30-20:00 (Kyiv time)

Duration of the course (lectures): 12 weeks

Lecturer: Pat Patton (MBA USA)

Language: English

ECTS: 5

Type of examination: Written assignment

Learning outcomes: By the end of this course, students will be able to:

Comprehend International Marketing Fundamentals: Gain a complete understanding of international marketing concepts and their application in real-world global marketing situations.

Analyze the Global Marketing Environment: Identify and evaluate cultural, economic, political, and legal factors that influence international marketing decisions.

Apply Global Trade Frameworks: Demonstrate knowledge of regional and international trade agreements and policies affecting global business operations.

Design International Marketing Strategies: Develop, critique, and implement effective marketing plans and strategies for international markets, including start-up and large-scale operations.

Leverage eCommerce & mCommerce: Integrate Internet marketing, global eCommerce, and mCommerce into international marketing plans.

Evaluate Social & Ethical Responsibilities: Assess and apply socially responsible marketing practices addressing long-term societal impact across borders.

Adapt to Global Marketing Changes: Respond to social media updates, currency fluctuations, and international forces such as demographics, geography, and psychographics.

Demonstrate Professional Skills: Present ideas clearly in written assignments, class discussions, and develop an individual marketing plan with measurable goals, objectives, and strategies.

Course content: The course is structured into five main parts with related discussions, assignments, and activities:

Part I: The International Marketing Environment

• Introduction, Orientation, and Overview

• Global marketing definitions and key concepts

• Cultural, economic, political, and legal environments in international markets

• Marketing planning fundamentals

Part II: International Trade Frameworks & Policy

• Regional and international trade agreements

• Global trade frameworks and policies

• Currency conversion issues in international marketing

• First written assignment 

Part III: The Global Marketing Mix

• Market entry strategies

• Advertising and public relations in international markets

• Internet marketing, eCommerce, and mCommerce applications

• Second written assignment

Part IV: Leadership in Global Marketing

• Leadership skills in international marketing

• Global marketing planning, goals, objectives, strategies, and implementation

• Discussion and updates on individual marketing plans

• Third written assignment 

Integration and Application

• Marketing plan reviews and presentations

• Case studies and group discussions

• Semester wrap-up and overview

• Final Individual Marketing Plan submission

Timetable: Mondays (6.10.2025-26.01.2026): 17:00-20:30 (Kyiv time)

Duration of the course (lectures): 10 weeks/30 hours

Lecturer: Dr. Mykola Hodovychenko

Language: Ukrainian

ECTS: -/1

Type of examination: Written assignment

Learning outcomes: Learners will be able to design and build modern Android apps in Kotlin using Jetpack Compose, Navigation, DI, and Coroutines/Flow. They will master clean MVVM architecture; data and background work (Room/Retrofit/WorkManager); testing (JUnit/Compose UI); profiling, security, accessibility, and Play Store release.

Course content: Modern Android stack: Kotlin, Jetpack Compose, Material 3, Navigation, Hilt, Coroutines/Flow, Room, Retrofit, WorkManager, DataStore. Architecture and modularization (MVVM, Clean Architecture), offline-first and caching, testing and CI/CD, performance optimization, security, localization & accessibility, and Play Console integration.

Timetable: Tuesdays, Fridays (7.10.2025-12.12.2025): 15:00-16:30

Duration of the course (lectures): 10 weeks/30 hours

Lecturer: Dr. Olga Matsuga (DNU)

Language: Ukrainian

ECTS: -/1

Type of examination: Written assignment

Learning outcomes: By the end of the course, students will be able to: 

• Understand the fundamental tasks and basic principles of supervised and unsupervised machine learning.

• Apply Python libraries such as pandas and scikit-learn for data preprocessing and model development. 

• Develop, train, and evaluate machine learning models using appropriate methods, metrics, and Python libraries.

Course content: Introduction to machine learning: key concepts and tasks.

• Data preprocessing: theory and hands-on exercises in pandas.

• Classification and regression: models, hyperparameters, model evaluation, overfitting, and practical exercises in scikit-learn.

• Clustering: methods, validation, and hands-on implementation in scikit-learn.

• Dimensionality reduction: overview with practical examples.

Timetable: Tuesdays, Wednesdays (1/2) (7.10.2025-10.12.2025): 15:30-17:30

Duration of the course (lectures): 10 weeks/30 hours

Lecturer: Dr. Maryna Ivanchenko (DNU)

Language: Ukrainian

ECTS: -/1

Type of examination: Written assignment

Learning outcomes: Learners will understand the core concepts and applications of deep learning, gaining hands-on experience in designing, training, and evaluating neural networks with TensorFlow. They will also acquire practical experience in applying ready-to-use models and in adapting pre-trained models to real-world tasks.

Course content: The course provides the foundations of building and training deep neural networks, along with an introduction to key architectures and techniques. It explores a range of applications such as classification, regression, computer vision, natural language processing and reinforcement learning, covering models from fully connected, convolutional and recurrent networks to GANs, Transformers and Large Language Models.

Timetable: Tuesdays, Wednesdays (7.10.2025-10.12.2025): 16:00-17:30

Duration of the course (lectures): 10 weeks/30 hours

Lecturer: Prof. Dr. Oleksandr Lemeshko (NURE)

Language: Ukrainian

ECTS: -/1

Type of examination: Written assignment

Learning outcomes:  Understanding the principles of network infrastructure protection; Knowledge of types of network attacks (DoS, MITM, spoofing, sniffing, etc.); Configuring Cisco switches and routers in accordance with security policies; Implementing VLAN, ACL, NAT, VPN, and IPSec to isolate and protect traffic; Detecting and mitigating attacks such as ARP spoofing, DHCP starvation, and MAC flooding.

Course content: Fundamentals of Network Security; LAN Security Techniques; WAN and Routing Security. 

Timetable: Thursdays, Saturdays (9.10.2025-18.12.2025): 16:30-18:00

Duration of the course (lectures): 10 weeks/30 hours

Lecturer: Prof. Dr. Mariia Skulysh (KPI)

Language: Ukrainian

ECTS: -/1

Type of examination: Written assignment

Learning outcomes: •    Understand the 5G Core architecture and the operation principles of key protocols (3GPP, GTP, Policy Control).

•    Analyze traffic control procedures and requirements for 5G base stations.

•    Evaluate the efficiency of resource utilization in modern telecommunication systems, including the radio interface and physical layer (modulation, channels, coding).

•    Apply open-source tools for testing 5G subsystems and analyzing network processes.

•    Utilize methods of virtualization, containerization, and computing resource management (Kubernetes, cloud infrastructures).

•    Implement monitoring systems and automated configuration management tools in high-load telecommunication services.

•    Apply mathematical methods for dynamic resource management, load balancing, and energy-efficient computing.

•    Analyze and implement modern concepts of Software-Defined Networking (SDN) and Network Function Virtualization (NFV).

Course content: 

1.      Introduction: the challenges of resource optimization in telecommunications

2.      5G Core architecture and analysis of 3GPP protocols

3.      Traffic and policy control (Policy Control)

4.      GPRS Tunneling Protocol in 5G

5.      Requirements for 5G base stations

6.      Physical layer of new radio interfaces (modulation, channels, coding)

7.      High-loaded services and Big Data management systems

8.      Infrastructure organization: containerization and virtualization

9.      Kubernetes and integrated solutions for computing infrastructure management

10.   Monitoring systems and configuration management tools (Ansible, Prometheus, etc.)

11.   Software-Defined Networking (SDN) and Network Function Virtualization (NFV)

12.   Mathematical methods of resource optimization: dynamic control and load balancing

13.   Methods for improving energy efficiency in telecommunication computing

14.   Case studies: optimization of 5G networks and data centers

15.   Future perspectives of resource management in 6G

Timetable: Thursdays (9.10.2025-18.12.2025): 16:00-18:00