Information Package / Course Catalogue
Digital Marketing and Artificial Intelligence
Course Code: İŞY267
Course Type: Area Elective
Couse Group: Short Cycle (Associate's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 0
Credit: 2
Lab: 0
ECTS: 2
Objectives of the Course

The aim of this course is to provide students with a comprehensive understanding of the fundamental concepts, tools, and strategies of digital marketing; to develop their ability to analyze digital consumer behavior and design and evaluate digital marketing campaigns; and to equip them with knowledge and practical skills in the application of artificial intelligence to digital marketing, including content creation, customer analytics, personalization, data privacy, and ethical issues.

Course Content

This course covers the fundamental concepts of digital marketing, the digital marketing environment and digital consumers, websites, search engine optimization (SEO) and search engine marketing (SEM), social media marketing, content marketing, email and mobile marketing, digital advertising and performance marketing, applications of artificial intelligence in marketing, AI-powered content creation, chatbots and virtual assistants, customer analytics and personalization, AI ethics, data privacy and security, and case studies on digital marketing and artificial intelligence applications.

Name of Lecturer(s)
Learning Outcomes
1.It explains the fundamental concepts and tools of digital marketing.
2.It evaluates digital marketing channels (search engines, social media, email, and mobile platforms) in terms of effectiveness.
3.It contributes to marketing decisions by analyzing digital consumer behavior.
4.It explains the uses of artificial intelligence technologies in digital marketing and demonstrates their basic applications.
5.It develops solutions by interpreting data related to digital marketing and artificial intelligence applications.
Recommended or Required Reading
1.Odabaşı, Y. (2024). Dijital Pazarlama. İstanbul: Cinius Yayınları.
2.Odabaşı, Y. (2023). Yeni Nesil Pazarlama. İstanbul: Cinius Yayınları.
3.Jim Sterne, J. (2017). Artificial Intelligence for Marketing: Practical Applications. Hoboken, NJ: John Wiley & Sons.
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to Digital Marketing and Basic Concepts
Week 1 - Preparation Work
Reading the relevant chapter from the course textbook.
Week 2 - Theoretical
Digital Marketing Environment and Digital Consumer
Week 2 - Preparation Work
Reading the relevant chapter from the course textbook.
Week 3 - Theoretical
Websites and Search Engine Marketing (SEO-SEM)
Week 3 - Preparation Work
Reading the relevant chapter from the course textbook.
Week 4 - Theoretical
Social Media Marketing
Week 4 - Preparation Work
Reading the relevant chapter from the course textbook.
Week 5 - Theoretical
Content Marketing and Content Strategies
Week 5 - Preparation Work
Reading the relevant chapter from the course textbook.
Week 6 - Theoretical
Email Marketing and Mobile Marketing
Week 6 - Preparation Work
Reading the relevant chapter from the course textbook.
Week 7 - Theoretical
Digital Advertising and Performance Marketing
Week 7 - Preparation Work
Reading the relevant chapter from the course textbook.
Week 8 - Theoretical
Digital Advertising and Performance Marketing
Week 8 - Preparation Work
Reading the relevant chapter from the course textbook.
Week 9 - Theoretical
Introduction to Artificial Intelligence and its Applications in Marketing
Week 9 - Preparation Work
Reading the relevant chapter from the course textbook.
Week 10 - Theoretical
AI-Powered Content Creation and Text Generation Tools
Week 10 - Preparation Work
Reading the relevant chapter from the course textbook.
Week 11 - Theoretical
Chatbots and Virtual Assistants
Week 11 - Preparation Work
Reading the relevant chapter from the course textbook.
Week 12 - Theoretical
Customer Analytics and Personalization with Artificial Intelligence
Week 12 - Preparation Work
Reading the relevant chapter from the course textbook.
Week 13 - Theoretical
Artificial Intelligence Ethics, Data Privacy and Security
Week 13 - Preparation Work
Reading the relevant chapter from the course textbook.
Week 14 - Theoretical
Digital Marketing and Artificial Intelligence Applications, Case Studies
Week 14 - Preparation Work
Reading the relevant chapter from the course textbook.
Assessment Methods and Criteria
Type of AssessmentCountPercent
Assignment1%5
Quiz1%5
Midterm Examination1%30
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory141242
Assignment1202
Quiz1101
Midterm Examination1101
Final Examination1303
TOTAL WORKLOAD (hours)49
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
PÇ-12
PÇ-13
PÇ-14
OÇ-1
2
5
2
2
3
4
2
2
2
2
1
2
2
4
OÇ-2
2
5
3
3
3
5
3
3
2
2
1
2
2
4
OÇ-3
3
5
3
4
5
4
4
3
3
3
1
2
2
3
OÇ-4
2
5
3
4
3
5
3
2
3
2
1
2
3
5
OÇ-5
3
5
3
5
4
5
5
4
3
4
1
2
3
5
Adnan Menderes University - Information Package / Course Catalogue
2026