International Trade and Business (English) | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code: | UNI438 | ||||
Course Name: | AI and Transformation Management | ||||
Semester: | Fall | ||||
Course Credits: |
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Language of instruction: | English | ||||
Course Condition: | |||||
Does the Course Require Work Experience?: | No | ||||
Type of course: | University Elective | ||||
Course Level: |
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Mode of Delivery: | E-Learning | ||||
Course Coordinator: | Öğr. Gör. SERTAÇ YERLİKAYA | ||||
Course Lecturer(s): | Dr.Sertaç Yerlikaya | ||||
Course Assistants: |
Course Objectives: | The course aims to equip participants with the knowledge and tools to understand how technology has transformed industries, societies, and individuals, while also identifying opportunities and addressing challenges in technology-driven change. The course seeks to develop awareness of AI’s interdisciplinary impact and encourage critical evaluation of its ethical, social, and political consequences. Through expert insights, students will gain a deeper understanding of AI’s real-world applications and implications. This course relies less on theory and more on practical applications in the industry. |
Course Content: | This course explores technological transformation from the Industrial Revolutions to Artificial Intelligence (AI), examining key concepts in transformation management. Students will analyze AI’s role across various disciplines and discuss its social, political, and ethical implications. Additionally, guest speakers from different industries will provide real-world insights into AI’s impact, offering practical perspectives on technology-driven change. |
The students who have succeeded in this course;
1) Understand historical and contemporary technological transformations: 2) Identify key principles of transformation management in tech-driven change: 3) Assess the opportunities and challenges presented by AI across industries: 4) Critically analyze AI’s business, social, ethical, and political implications: 5) Apply transformation management strategies to real-world scenarios: |
Week | Subject | Related Preparation |
1) | Introduction to AI and Transformation Management Course | Students are expected to thoroughly review the course syllabus to understand the overall structure and objectives of the class. |
2) | Industry 4.0/5.0 | This week serves as an introduction to understanding the concept of transformation and learning the foundational elements of Industry 4.0 and 5.0. Before coming to class, explore studies that show how transformation affects not only technology but also society and individuals. Explore how technological transformation is unfolding in your own field (e.g., business, healthcare, engineering, arts) and follow current debates on how these changes are being discussed. |
3) | Drivers and Challenges of Technology Transformation | Review your notes from Week 2. Reflect on the factors that drive transformation and common challenges faced by organizations. Read Andrew Ng’s How to Choose Your First AI Project and the introduction of Leading Digital. |
4) | Transformation Management – Alignment with Strategy | Revise notes from Week 3 on innovation. Learn how digital transformation aligns with organizational strategy. Read “Digital Transformation Is Not About Technology” and “Digital Transformation Is About Talent, Not Technology.” |
5) | Innovation Management – Problem-Solving in Transformation | Review the concepts of Week 4. Research innovation types and organizational problem-solving strategies. Explore case studies showing innovation under transformation pressures. Prepare your questions about Innovation Management for guest speaker. |
6) | Introduction to AI – Concepts, History, and Trends | Review the strategy and transformation alignment topics from Week 5. Study the history and current uses of artificial intelligence . Preapre your questions for guest speaker. |
7) | Fundamentals of AI and Machine Learning | Revisit AI concepts from Week 6, and read documents shared. Explore basic ML concepts: supervised/unsupervised learning, key algorithms, and model training. Prepare your questions for guest speaker. |
8) | Midterm - proje | Begin by reviewing all course materials covered up to this point to ensure a solid understanding of the key concepts. Form your group, ideally with a minimum of 8 students from diverse faculties to encourage interdisciplinary collaboration. Each group will present an initial draft of their final paper to receive feedback. Prepare a clear and engaging presentation that addresses a transformation challenge within your field of study and proposes a practical, AI-driven solution. Focus on clearly defining the problem, demonstrating the relevance and feasibility of the AI application, and highlighting the interdisciplinary impact of your approach. |
9) | Challenges in Scaling AI in Organizations (Panel Discussions) | This week features panel discussions with industry leaders on the real-world challenges of scaling AI within organizations. To prepare, review what you've learned about AI implementation barriers such as data readiness, organizational culture, and talent gaps. Prepare questions that connect these topics with your own field of study. During the session, take notes and reflect on how these challenges apply to both large and small organizations. |
10) | Group Project Presentations | Prepare your projects as defined. Organize your team according to a 5-minute presentation and 2-minute Q&A format. Make sure to rehearse in advance. |
11) | Con't- Group Project Presentations | Ref :Week 10 |
12) | Responsible AI | This week focuses on the ethical, transparent, fair, and accountable development and use of artificial intelligence systems. Review the concepts discussed in class and explore current articles on issues such as algorithmic bias, privacy, and decision-making accountability. Reflect on how AI applications in your own field may create responsibilities or ethical concerns. Be ready to discuss how human rights, data security, and social equity should be considered in the design and deployment of AI technologies. Try to approach the concept of "responsible AI" not only from a technical standpoint but also from social and institutional perspectives. |
13) | The Role of Humans in a Trasnformed World | For this week, reflect on how the rapid advancement of AI is reshaping the role of humans in the workforce and society. Review class discussions on human-AI collaboration, skill transformation, and the future of work. Read the materials provided and consider how your field is adapting to human-machine interaction. Be prepared to discuss how human creativity, ethics, and emotional intelligence continue to provide value in a technology-driven world. |
14) | AI and Its Evolving Landscape | This week focuses on understanding the constantly changing AI landscape. Explore recent trends such as generative AI, AI agents, and advances in large language models. Review the course materials and connect them with the latest news or breakthroughs you find through reputable sources (e.g., MIT Tech Review, Stanford AI Index). Reflect on how this evolution impacts your own field and be ready to share relevant examples. |
15) | Revision | |
16) | final week |
Course Notes / Textbooks: | Lecturer's Notes, Ders Notları |
References: | Ders süresince sağlanacak seçilmiş makaleler ve vaka çalışmaları Selected articles and case studies (provided throughout the course) |
Course Learning Outcomes | 1 |
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3 |
4 |
5 |
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Program Outcomes | |||||||||||||
1) Has a broad and interdisciplinary perspective on international business and trade by the use of social sciences and mathematics, | |||||||||||||
2) Possess the knowledge and skills related to different functions and interactions of international business and trade. | |||||||||||||
3) Possess the knowledge and skills to interpret the data, concepts and ideas in the field of international business and trade with scientific and technological methods. | |||||||||||||
4) Use different theoretical approaches to understanding and solving various business and trade problems. | |||||||||||||
5) Explains the competitiveness of the countries with the requirements of international competition and interprets the functioning of the actors and regulatory structures in the international environment. | |||||||||||||
6) Understands the value of developing new trade projects and generating strategies within international market needs. | |||||||||||||
7) Solves complex business and global trade problems by using various statistical techniques and numerical methods and makes analyzes by using statistical programs effectively. | |||||||||||||
8) Uses a foreign language at the B1 General Level in terms of European Language Portfolio criteria according to the level of education. | |||||||||||||
9) Develops teamwork, negotiation, leadership and entrepreneurship skills. | |||||||||||||
10) Possess the knowledge of universal ethical values, social responsibility and sufficient legal and regulatory knowledge. | |||||||||||||
11) Develops positive attitudes related to lifelong learning and identifies individual learning needs and carries out studies to correct them. | |||||||||||||
12) Students will be able to communicate their ideas and solutions both written and orally, and present and publish them on both national and international platforms. | |||||||||||||
13) Uses information and communication technologies together with computer software at the advanced level of European Computer Using License required by the field. |
No Effect | 1 Lowest | 2 Average | 3 Highest |
Program Outcomes | Level of Contribution | |
1) | Has a broad and interdisciplinary perspective on international business and trade by the use of social sciences and mathematics, | |
2) | Possess the knowledge and skills related to different functions and interactions of international business and trade. | |
3) | Possess the knowledge and skills to interpret the data, concepts and ideas in the field of international business and trade with scientific and technological methods. | |
4) | Use different theoretical approaches to understanding and solving various business and trade problems. | |
5) | Explains the competitiveness of the countries with the requirements of international competition and interprets the functioning of the actors and regulatory structures in the international environment. | |
6) | Understands the value of developing new trade projects and generating strategies within international market needs. | |
7) | Solves complex business and global trade problems by using various statistical techniques and numerical methods and makes analyzes by using statistical programs effectively. | |
8) | Uses a foreign language at the B1 General Level in terms of European Language Portfolio criteria according to the level of education. | |
9) | Develops teamwork, negotiation, leadership and entrepreneurship skills. | |
10) | Possess the knowledge of universal ethical values, social responsibility and sufficient legal and regulatory knowledge. | |
11) | Develops positive attitudes related to lifelong learning and identifies individual learning needs and carries out studies to correct them. | |
12) | Students will be able to communicate their ideas and solutions both written and orally, and present and publish them on both national and international platforms. | |
13) | Uses information and communication technologies together with computer software at the advanced level of European Computer Using License required by the field. |
Semester Requirements | Number of Activities | Level of Contribution |
Attendance | 14 | % 15 |
Quizzes | 5 | % 10 |
Project | 15 | % 30 |
Seminar | 6 | % 5 |
Final | 1 | % 40 |
total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 60 | |
PERCENTAGE OF FINAL WORK | % 40 | |
total | % 100 |
Activities | Number of Activities | Workload |
Course Hours | 14 | 56 |
Homework Assignments | 2 | 10 |
Quizzes | 8 | 32 |
Final | 4 | 17 |
Total Workload | 115 |