
| Course Code | : İKT418 |
| Course Type | : Area Elective |
| Couse Group | : First Cycle (Bachelor's Degree) |
| Education Language | : Turkish |
| Work Placement | : N/A |
| Theory | : 3 |
| Prt. | : 0 |
| Credit | : 3 |
| Lab | : 0 |
| ECTS | : 5 |
The aim of this course is to enable students to understand the economic, social, and institutional impacts of digital transformation and artificial intelligence technologies, and to develop the ability to effectively use artificial intelligence applications in economic analysis, data evaluation, decision making, and policy development processes.
Concepts of digital transformation and their economic impacts; digital economy and platform economies; Industry 4.0 and smart production systems; big data and data economy; fundamental concepts of artificial intelligence and machine learning; generative artificial intelligence applications; effective prompt engineering techniques; the use of artificial intelligence in academic research; AI assisted data analysis and reporting tools; the effects of artificial intelligence on labor markets, financial markets, and public policies; data security, ethics, and regulatory frameworks; artificial intelligence applications in economic analysis and contemporary case studies.
| 1. | Explain the fundamental concepts of digitalization, digital transformation, and artificial intelligence technologies and their effects on economic systems. |
| 2. | Evaluate and interpret economic problems using artificial intelligence and data driven analytical tools. |
| 3. | Analyze current developments in the digital economy, platform economies, and financial technologies. |
| 4. | Use generative artificial intelligence tools and effective prompt engineering techniques for academic and professional purposes. |
| 5. | Develop solution proposals by evaluating the ethical, legal, and social dimensions of artificial intelligence applications. |
| 1. | Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4th Edition). |
| 2. | Current academic articles, case studies, and artificial intelligence applications provided by the lecturer. |
| Type of Assessment | Count | Percent |
|---|---|---|
| Project | 1 | %10 |
| Quiz | 1 | %10 |
| Midterm Examination | 1 | %20 |
| Final Examination | 1 | %60 |
| Activities | Count | Preparation | Time | Total Work Load (hours) |
|---|---|---|---|---|
| Lecture - Theory | 14 | 2 | 3 | 70 |
| Lecture - Practice | 4 | 2 | 3 | 20 |
| Quiz | 2 | 8 | 1 | 18 |
| Midterm Examination | 1 | 7 | 1 | 8 |
| Final Examination | 1 | 8 | 1 | 9 |
| TOTAL WORKLOAD (hours) | 125 | |||
PÇ-1 | PÇ-2 | PÇ-3 | PÇ-4 | PÇ-5 | PÇ-6 | PÇ-7 | |
OÇ-1 | 4 | 4 | 4 | 4 | 5 | 4 | 4 |
OÇ-2 | 3 | 5 | 3 | 3 | 3 | 5 | 5 |
OÇ-3 | 4 | 3 | 3 | 4 | 4 | 5 | 5 |
OÇ-4 | 5 | 5 | 5 | 4 | 4 | 4 | 4 |
OÇ-5 | 3 | 3 | 3 | 3 | 3 | 4 | 3 |