CUFE Business School provide 3 courses in the 2024 CUFE International Summer School. All courses will be delivered in classroom.

Course description

Doing business in the CEE

People’s Republic of China (hereinafter referred to as China) is currently the world’s second biggest economy and an increasingly important player in global affairs. The CEE countries represent a significant part of the EU as well as of the emerging Europe. Both regions share many similarities in their economic, political and historical development. At the same time, however, fundamental differences between the regions exist in their current economic, political and strategic thinking.

The aim of the course is to provide framework for understanding the CEE region with emphasis to the Czech Republic that will enable Chinese students and professionals to do business with CEE countries more efficiently and successfully.

The course structure

1) The course first looks into similarities and differences between the two regions within the framework of international political economy, with the emphasis on comparing the systems.

2) In the second part, recent cooperation between China and the CEE under the 14+1 and Belt and Road framework is discussed and analysed.

3) Building and expanding the previous parts, the last part is focused on practical business insight related to China-CEE economic cooperation where students will have to use synthesis of the knowledge gained in order to demonstrate that they can successfully do business in the CEE (with focus on the Czech Republic)

Learning outcomes and competences

Upon successful completion of the course, students will:

- Understand the development of international economic and political relations

between the two regions (CEE and China)

- Analyse the current development of international trade between China and the CEE

- Identify the future potential in economic relations between China and CEE

- Critically evaluate current Czech-Chinese trade and investment projects

- Understand the specifics of doing business in the CEE

- Understand the difficulties of Chinese companies in CEE

- Understand the difficulties of CEE in China

- Be able to form successful cooperation with their CEE counterparts

Final exam proposition

Project presentation where students need to demonstrate understanding of the topic thoroughly. Students are expected to play active part throughout the course.

Lecturer profile:

Prof. Jan Bejkovsky, Deputy Director of the Center for Asian Studies at Charles University of the Czech Republic, Director of the China Czech Trade Promotion Agency in Beijing, and invited research expert on Central and Eastern Europe for the Shandong Provincial Government.

Hours and credits: 32 hours, 2 credits

Time (Beijing time):

Week 20, July 8-12, 8.30-11.30 a.m. and 14.00-17.00 p.m.

1.2 Foundations of Data Science

At the end of the module, participants will gain a solid foundation in data science and analytics using Python, equipping them with the necessary knowledge and skills to embark on data driven projects and pursue further studies or careers in the field of data science. No prior knowledge of programming and/or statistics is needed.

Syllabus:

Introduction to data science is and how it integrates business, programming, and statistical analysis domains 2. Introduction to Python 3. Introduction to Statistics 4. Introduction to Machine Learning

Learning outcomes:

Understanding of Data Science: Participants will gain a comprehensive understanding of what data science entails and how it intersects with business, programming, and statistical analysis domains. They will grasp the significance of data science in various industries and its applications. 2. Proficiency in Python: Participants will acquire essential Python programming skills necessary for data analysis and manipulation. They will learn how to write Python code eNiciently to handle and analyse data, as well as implement various data science techniques. 3. Basic Statistical Analysis: Participants will be introduced to fundamental statistical concepts and techniques essential for data analysis. They will learn how to interpret and analyse data using statistical methods, as well as apply statistical tests to make datadriven decisions. 4. Introduction to Machine Learning: Participants will be introduced to the core concepts of machine learning and its applications in data science. They will understand various machine learning algorithms and techniques, such as classification, regression, clustering, and dimensionality reduction. Through case studies, they will learn how to apply machine learning algorithms to real-world datasets and solve practical problems.  

Lecturer profile:

Prof. Ufuk Gunes Bebek is an applied economist whose research is primarily focused on international trade and macroeconomic aspects of international trade. He joined the University of Birmingham's Department of Economics in 2014.

Hours and credits: 32 hours, 2 credits

Time (Beijing time):

Week 19, July 1-5, 8.30-11.30 p.m. Week 20, July 8-12, 8.30-11.30 p.m.

1.3 Working in teams

The course aims to theoretically frame the issues of working in a group and practically develop relational skills and group management capabilities, with an emphasis on both physical and virtual environments.

The module provides a theoretical overview of key elements that can influence group work such as personality, behavioral role preference, leadership styles, and the management of communication and conflict. These theoretical aspects are essential to enhance students’ awareness and knowledge of the topics under analysis, paving the way for comprehensive personal development. In addition to knowledge enhancement, the module aims to develop students' abilities to ‘decode’ social contexts in which they find or will find themselves at work—both onsite and online—and how these contexts affect them. Through "decoding" skills, students will be stimulated to develop reactive and managerial capabilities applicable to these social work contexts. Adding a new dimension, the course will introduce the leadership of virtual teams. This part focuses on setting clear objectives that align team efforts in a virtual setting, understanding and managing the dynamics of interpersonal relationships remotely, and fostering self-management and personal accountability. Students will learn how to effectively lead virtual teams, addressing unique challenges such as virtual communication barriers, cultural differences, and the need for technology proficiency.

For these reasons, the module heavily relies on practical exercises and simulations, using an experiential learning approach in both physical and virtual setups. The learning path is divided into 3 sections:

Section I: Creation and composition of groups, including virtual teams.

Section II: Management of the group and its members.

Section III: A focus on virtual leadership skills.

Lecturer profile:

Massimiliano M. Pellegrini is an Associate Professor of Organizational Studies and Entrepreneurial Behaviour at the University of Rome “Tor Vergata”. He currently coordinates two tracks at the European Academy of Management (EURAM), where he chaired the Strategic Interest Group on Entrepreneurship (E-ship SIG) until 2018. He is the Editor-in-Chief of the International Journal of Globalisation and Small Business (ABS 1*), an editor for the 'Entrepreneurial Behaviour' book series (Emerald Publishing), and an Associate Editor for the Journal of Management and Organization, Strategic Change, Journal of Enterprising Communities, Heliyon – Business Management Section, and the International Journal of Transition and Innovation Systems. His interests include decision-making processes and behaviors, especially in relation to digital transformation. He has published in highly ranked journals such as IEEE Transactions on Engineering Management, International Small Business Journal, Journal of Business Ethics, Journal of Business Research, Journal of Small Business Management, Small Business Economics, and Technovation.

Hours and credits: 32 hours, 2 credits

Time:

Week 19, July 2-5, 13.30-17.00. Week 20, July 8-12, 13.30-17.00

How to apply?

All CUFE students are welcome to apply through the university class selection platform.