Information Package / Course Catalogue
| Course Code | : HIT025 |
| Course Type | : Area Elective |
| Couse Group | : Short Cycle (Associate's Degree) |
| Education Language | : Turkish |
| Work Placement | : N/A |
| Theory | : 1 |
| Prt. | : 2 |
| Credit | : 2 |
| Lab | : 0 |
| ECTS | : 3 |
The aim of this course is to provide students with an understanding of the fundamental principles of artificial intelligence and generative artificial intelligence systems, and to develop their ability to effectively use AI tools in public relations, corporate communication, advertising, publicity, media, content creation, research, and reporting processes. The course also aims to enable students to evaluate AI-generated outputs in terms of accuracy, reliability, originality, ethical considerations, and professional suitability; and to develop human-centered workflows based on human oversight while protecting personal data and organizational information.
The course covers AI literacy, generative artificial intelligence, large language models, selection of AI tools, prompt design, information search and verification, professional text generation, social media content creation, advertising and visual design, audio and video production, presentation preparation, data analysis, reporting, media monitoring, automation, AI-supported assistants, ethics, copyright, personal data protection, algorithmic bias, disinformation, and AI-supported professional project development.
| 1. | Yapay zekâ, makine öğrenmesi, üretken yapay zekâ ve büyük dil modeli kavramlarını açıklar. |
| 2. | Mesleki bir görev için uygun yapay zekâ aracını ve çalışma yöntemini belirler. |
| 3. | Yapay zekâ desteğiyle basın, medya, kurumsal iletişim ve sosyal medya içerikleri hazırlar. |
| 4. | Yapay zekâ araçlarından yararlanarak reklam ve görsel iletişim fikirleri geliştirir. |
| 5. | Yapay zekâ destekli temel iş akışları ve mesleki uygulamalar tasarlar. |
| 6. | Kişisel veriler, kurumsal gizlilik, telif hakları ve mesleki etik kurallarına uygun ürünler oluşturur. |
| 1. | Gökçearslan, Şahin ve Hatice Yıldız Durak (Ed.). Yapay Zekâ Okuryazarlığı. Nobel Akademik Yayıncılık, 2024. |
| 2. | Nabiyev, Vasif ve Ali Kürşat Erümit (Ed.). Üretken Yapay Zekâ ve Uygulamaları: Dil Modelleri, Prompt Yazma, Üretken Yapay Zekâ Uygulamaları. Seçkin Yayıncılık, 2025. |
| Type of Assessment | Count | Percent |
|---|---|---|
| Assignment | 1 | %5 |
| Term Assignment | 1 | %5 |
| Midterm Examination | 1 | %30 |
| Final Examination | 1 | %60 |
| Activities | Count | Preparation | Time | Total Work Load (hours) |
|---|---|---|---|---|
| Lecture - Theory | 14 | 1 | 1 | 28 |
| Lecture - Practice | 14 | 1 | 2 | 42 |
| Assignment | 1 | 3 | 0 | 3 |
| Term Project | 1 | 3 | 0 | 3 |
| Midterm Examination | 1 | 0 | 1 | 1 |
| Final Examination | 1 | 0 | 1 | 1 |
| TOTAL WORKLOAD (hours) | 78 | |||
PÇ-1 | PÇ-2 | PÇ-3 | PÇ-4 | PÇ-5 | PÇ-6 | |
OÇ-1 | 3 | 3 | 3 | 3 | 3 | 3 |
OÇ-2 | 3 | 3 | 3 | 3 | 3 | 3 |
OÇ-3 | 3 | 3 | 3 | 3 | 3 | 3 |
OÇ-4 | 3 | 3 | 3 | 3 | 3 | 3 |
OÇ-5 | 3 | 3 | 3 | 3 | 3 | 3 |
OÇ-6 | 3 | 3 | 3 | 3 | 3 | 3 |