ISTINYE UNIVERSITY BİLGİ PAKETİ / DERS KATALOĞU
| Management Information Systems (English) | |||||
| Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 | ||
Course Introduction and Application Information
| Course Code: | MIS076 | ||||
| Course Name: | Exploring Generative AI and Its Applications | ||||
| Semester: | Fall | ||||
| Course Credits: |
|
||||
| Language of instruction: | English | ||||
| Course Condition: | |||||
| Does the Course Require Work Experience?: | No | ||||
| Type of course: | Departmental Elective | ||||
| Course Level: |
|
||||
| Mode of Delivery: | E-Learning | ||||
| Course Coordinator: | Doç. Dr. OKAN YAŞAR | ||||
| Course Lecturer(s): |
Dr. Öğr. Üy. OZAN EVKAYA |
||||
| Course Assistants: |
Course Objective and Content
| Course Objectives: | This course aims to provide students with a comprehensive understanding of generative artificial intelligence technologies and their applications. We will delve into the theoretical underpinnings and practical methodologies of generative models, including VAEs, GANs, and Transformers. The course will equip students with the necessary knowledge to analyze and implement generative AI in various domains while addressing the ethical implications and the potential future developments in the field. |
| Course Content: | 1. Introduction to Generative AI: Definition, History, and Key Concepts 2. Deep Learning Foundations for Generative AI: Neural Networks and Backpropagation 3. Generative Models: Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Transformers 4. Applications of Generative AI: Content Creation, Data Augmentation, and Personalization 5. Ethical Considerations and Future Trends in Generative AI |
Learning Outcomes
|
The students who have succeeded in this course;
1) 1. Grasp the fundamental concepts and theories behind generative artificial intelligence. 2) 2. Demonstrate proficiency in building and evaluating various generative models. 3) 3. Apply generative AI technologies to real-world applications and problem-solving. 4) 4. Critically analyze the societal and ethical ramifications of deploying generative AI. 5) 5. Stay current with the latest advancements and research trends in generative AI. |
Course Flow Plan
| Week | Subject | Related Preparation |
| 1) | 1. Yapay Zekaya Genel Bakış ve Üretken Yapay Zekaya Giriş | |
| 2) | 2. Understanding Machine Learning Fundamentals for AI Generation | |
| 3) | 3. Core Concepts in Neural Networks and Their Role in Generative AI | |
| 4) | 4. Exploring Backpropagation and Its Importance to Generative Models | |
| 5) | 5. An In-Depth Look at Variational Autoencoders (VAEs) | |
| 6) | 6. Diving into Generative Adversarial Networks (GANs) and Their Mechanics | |
| 7) | 7. Studying the Role of Transformers in Generative AI | |
| 8) | 8. **Midterm Exam** | |
| 9) | 9. Applications Part 1: Generative AI in Content Creation (Images, Music, Text) | |
| 10) | 10. Applications Part 2: Using Generative AI for Data Augmentation and Analysis | |
| 11) | 11. Applications Part 3: Personalization and Recommendation Systems via Generative AI | |
| 12) | 12. Advanced Topics in Generative Models: Fine-Tuning and Transfer Learning | |
| 13) | 13. The Social Impact of Generative AI: Ethical Aspects and Bias | |
| 14) | 14. Future Perspectives: Directions and Challenges in Generative AI Research | |
| 15) | 15. Discussions: Current Events, the State of the Art, and Emerging Technologies | |
| 16) | 16. **Final Exam** |
Sources
| Course Notes / Textbooks: | - |
| References: | - |
Course - Program Learning Outcome Relationship
| Course Learning Outcomes | 1 |
2 |
3 |
4 |
5 |
||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Program Outcomes | |||||||||||||
| 1) It has a wide range of interdisciplinary approaches to management information systems, primarily business and computer engineering. | 3 | 3 | 3 | 3 | 3 | ||||||||
| 2) Comprehends the management information systems in terms of technical, organizational and managerial aspects and uses the current programming language by knowing the logic of programming. | 3 | 3 | 3 | 3 | 3 | ||||||||
| 3) Uses different information technologies and systems for understanding and solving various business problems. | 3 | 3 | 3 | 3 | 3 | ||||||||
| 4) Interpret the data, concepts and ideas in the field of management information systems with scientific and technological methods. | 3 | 3 | 3 | 3 | 3 | ||||||||
| 5) Analyze the needs for an information system and analyze the processes of analysis, design and implementation of the database. | 3 | 3 | 3 | 3 | 3 | ||||||||
| 6) Gains technical and managerial contributions to IT projects and takes responsibility. | 3 | 3 | 3 | 3 | 3 | ||||||||
| 7) Solve complex business and informatics problems by using various statistical techniques and numerical methods and make analyzes using statistical programs effectively. | 3 | 3 | 3 | 3 | 3 | ||||||||
| 8) Uses a foreign language at the B1 General Level in terms of European Language Portfolio criteria according to the level of education. | 3 | 3 | 3 | 3 | 3 | ||||||||
| 9) Develops teamwork, negotiation, leadership and entrepreneurship skills. | 3 | 3 | 3 | 3 | 3 | ||||||||
| 10) Has universal ethical values, social responsibility awareness and sufficient legal knowledge. | 3 | 3 | 3 | 3 | 3 | ||||||||
| 11) Develops positive attitudes related to lifelong learning and identifies individual learning needs and carries out studies to correct them. | 3 | 3 | 3 | 3 | 3 | ||||||||
| 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. | 3 | 3 | 3 | 3 | 3 | ||||||||
| 13) It uses information and communication technologies together with computer software at the advanced level of European Computer Driving License required by the field. | 3 | 3 | 3 | 3 | 3 | ||||||||
Course - Learning Outcome Relationship
| No Effect | 1 Lowest | 2 Average | 3 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | It has a wide range of interdisciplinary approaches to management information systems, primarily business and computer engineering. | 3 |
| 2) | Comprehends the management information systems in terms of technical, organizational and managerial aspects and uses the current programming language by knowing the logic of programming. | 3 |
| 3) | Uses different information technologies and systems for understanding and solving various business problems. | 3 |
| 4) | Interpret the data, concepts and ideas in the field of management information systems with scientific and technological methods. | 3 |
| 5) | Analyze the needs for an information system and analyze the processes of analysis, design and implementation of the database. | 3 |
| 6) | Gains technical and managerial contributions to IT projects and takes responsibility. | 3 |
| 7) | Solve complex business and informatics problems by using various statistical techniques and numerical methods and make analyzes using statistical programs effectively. | 3 |
| 8) | Uses a foreign language at the B1 General Level in terms of European Language Portfolio criteria according to the level of education. | 3 |
| 9) | Develops teamwork, negotiation, leadership and entrepreneurship skills. | 3 |
| 10) | Has universal ethical values, social responsibility awareness and sufficient legal knowledge. | 3 |
| 11) | Develops positive attitudes related to lifelong learning and identifies individual learning needs and carries out studies to correct them. | 3 |
| 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. | 3 |
| 13) | It uses information and communication technologies together with computer software at the advanced level of European Computer Driving License required by the field. | 3 |
Assessment & Grading
| Semester Requirements | Number of Activities | Level of Contribution |
| Midterms | 1 | % 40 |
| Final | 1 | % 60 |
| total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 40 | |
| PERCENTAGE OF FINAL WORK | % 60 | |
| total | % 100 | |
Workload and ECTS Credit Calculation
| Activities | Number of Activities | Workload |
| Course Hours | 14 | 42 |
| Midterms | 8 | 36 |
| Final | 8 | 50 |
| Total Workload | 128 | |