Programme of the Codeshare Teaching and Learning Summer School 2025

TRACK A: Sustainability

A1) Sustainable Strategy Lab: Crafting Sustainability Strategies and Applying Them in Real Cases

Prof. Dr. Simone Bernatzky, Bonn-Rhein-Sieg University of Applied Sciences

Time: 01:00 - 05:00 PM (CEST)
Maximum number of participants: 20

Description: 

The course explores the critical role of strategic planning in advancing Corporate Social Responsibility (CSR) and sustainable business practices. Participants will gain insights into the essential tools and processes for developing effective CSR strategies, with a strong focus on stakeholder engagement and the contextual factors that influence sustainability efforts. The course addresses practical challenges in CSR implementation and provides hands-on opportunities to analyze and assess real-world sustainability strategies from major companies.

Students will learn how to craft strategic recommendations that align environmental and social goals with core business objectives and diverse stakeholder interests. By the end, participants will be equipped to approach sustainability as a strategic, value-driven function within organizations.

TRACK B: Data Science

B1) Intelligent Insights: Mastering Chat GPT and other AI  Applications in Science and Business

Prof. Dr. Ralf Meyer, Bonn-Rhein-Sieg University of Applied Sciences

Time: 01:00 – 05:00 PM (CEST)
Maximum number of participants: 40

Description: 

“Intelligent Insights: Mastering Chat GPT and Other AI Applications in Science and Business" is an engaging and comprehensive five-day course that delves deeply into the fascinating world of artificial intelligence. This course primarily focuses on the revolutionary GPT technology and its wide array of applications across various fields. Participants will explore how AI is transforming international business practices and scientific research methodologies, providing a blend of theoretical knowledge and practical skills. The course offers hands-on experience with cutting-edge AI tools, including OpenAI's GPT. Throughout the course, students will learn to harness the full potential of these advanced AI tools, applying them in diverse, real-world contexts.

The curriculum also includes a critical examination of AI ethics and the societal implications of widespread AI adoption, fostering a balanced understanding of technology. By the end of the course, participants will not only comprehend the theoretical foundations of AI but also effectively apply these powerful tools in their university studies and professional careers, enhancing their problem-solving capabilities and decision-making processes in their respective fields.

TRACK C: Business and Management

C1) Design Thinking and Innovation

Oghenekome Umuerri, Bonn-Rhein-Sieg University of Applied Sciences

Time: 09:00 AM – 13:00 PM (CEST)
Maximum number of participants: 15

Description: 

Unlock your creative potential and drive innovation with our "Design Thinking and Innovation" course. This immersive program is designed to equip you with a robust understanding of the design thinking process, a human-centered approach to problem-solving that has been adopted by leading organizations worldwide.

Through a combination of theoretical insights and practical applications, you will learn to empathize with users, define problems, ideate creatively, prototype solutions, and test them rigorously. The course is structured to foster a collaborative environment where students can explore new ideas, challenge assumptions, and develop innovative solutions to real-world challenges

TRACK C1/2: Business and Management

C2) International Career Building

Jens Andreas Faulstich, Hochschule Koblenz

Time: 09:00 AM – 01:00 PM (CEST)
Maximum number of participants: max. 20 per participating institution (in total = 60 participants)

Description: 

• Strategic planning of international projects and activities in academic contexts (short-term/
  long-term; student exchange or internship;
  thesis projects in other countries and cultures)
• Effective job search methods in different regional and cultural environments (CV / resume writing; anti-discrimination policies in the HR sector; the role of social platforms and internship/job search engines in international career development)
• Interview practices and simulated job interviews
• Selected assessment centre tasks
• Culture at work (hierarchies; written and
  unwritten rules of conduct; formal and
  informal communication styles)

After completing this course, students

• know about job search methods in selected countries and cultural environments
• are able to write convincing letters of motivation, CVs and resumes
• are familiar with typical interview questions
  and are able to answer them in English
• are familiar with selected assessment centre tasks
• are aware of some cultural differences they need to
  expect and know some strategies for successful
  integration in an international work environment.

TRACK A: Sustainability

A2) Financing the Circular Economy

Prof. Dr. Daniel Agyapong, University of Cape Coast

Time: 09:00 AM - 01:00 PM (CEST)
Maximum number of participants: 40

Description: 

The course explores the financial mechanisms and strategies necessary to support and sustain a circular economy. Students will delve into the principles of circular economy, examine innovative financing models, and understand the economic, social, and environmental impacts of transitioning from a linear to a circular economic model. By integrating case studies, theoretical frameworks, and practical applications, this course equips students with the tools to drive sustainable financial solutions.

In this course, you will look at:

• Introduction to the Circular Economy
• Innovative Financing Models for the Circular Economy
• Economic and Environmental Impact Analysis

• Case Studies in Circular Economy Financing

TRACK C: Data Science

B2) Big Data Projects in Finance

Prof. Dr. Jack Woo

Time: 09:00 AM – 01:00 PM (CEST)
Maximum number of participants: max. 20 per participating institution

Description:

Big (alternative) data and machine learning (ML) become essential components of the modern investment process. However, not all datasets are necessarily useful for financial applications, and not all ML techniques can be applied on a “plug-and-play” basis. This course aims to provide the candidates with basic concepts, practical examples, use cases, and latest research projects of big data and ML in finance and investments. The course offers hands-on practice of using Python in quantitative finance applications. It allows the candidate to integrate their domain knowledge of finance into tactical algorithmic strategies and quickly come up to speed on the latest developments in quantitative investment using big data and ML applications.

By completing this course, the candidate should be able to:

• describe aspects of “fintech” that are directly relevant for the gathering and analyzing of financial data.
• describe big data, artificial intelligence, and machine learning
• describe applications of big data and data science to investment. management

TRACK A: Sustainability

A3) Sustainable Start-up Entrepreneurship

Prof. Dr. Jan-Thomas Bachmann, Bonn-Rhein-Sieg University of Applied Sciences

Time: 09:00 AM - 01:00 PM (CEST)
Maximum number of participants: 40

Description: 

In this course, students will learn the theoretical fundamentals of sustainable start-up entrepreneurship as well as how to turn their own business idea into a business model and, subsequently, a business plan. Furthermore, they will learn how to present their business plan in a convincing pitch. Students will consistently work in teams.

After completing this course, students will be able to:

• apply methods for the generation and selection of sustainable start-up ideas,
• apply methods and tools to analyze and evaluate the opportunities and risks of business start-ups,
• design a business model and a business plan,

• pitch their business plan to investors.