Information Package
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Program of Tourism and Hotel Management

SBMO134

GENERATIVE ARTIFICIAL INTELLIGENCE APPLICATIONS

Course Code
SBMO134
Semester
-
Theory+Practice
3 + 0
ECTS
4
Course TypeElective Course
Course LevelAssociate Degree
Year of Study-
Semester-
ECTS4
Name of Lecturer(s) -
Learning Outcomes

At the end of this course, the students;

  1. Identifies the functions, limitations, and applications of generative AI.technologies.
  2. Explains the contributions of AI tools in office management.
  3. Understands AI applications in the context of digital literacy and 21st-century skills.
  4. Distinguishes the role of AI tools in virtual secretaryship and digital assistance.
  5. Explains data privacy, copyright, and ethical principles; develops awareness of responsible use.
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme Components
Course DescriptionThis course features advanced technology-oriented content covering the use of artificial intelligence technologies in creative processes and professional life. Within its framework, large language models, visual production tools, automation techniques, and AI ethics are addressed. The primary objective is to provide students with the competence to increase their productivity using AI tools and to lead digital transformation.
Course Contents
WEEK TOPICS
1st Week Introduction to the course, objectives, and scope. General framework of digital transformation and AI concepts
2nd Week 21st-century skills and digital literacy. Changing roles in office environments
3rd Week Introduction to generative AI: basic concepts, mechanisms, opportunities, and limitations
4th Week Types of AI tools: text, visual, audio, presentation generation
5th Week Text generation in office management: email drafts, official documents, note-taking
6th Week AI support in presentation and content design. Introduction to visual generation tools
7th Week Meeting planning, task management, and AI-assisted digital secretaryship
8th Week Midterm exam
9th Week Ethical principles in AI use: transparency, responsibility, copyright, plagiarism
10th Week Data privacy and security: protection of personal data, institutional risks
11th Week Future job roles in virtual secretaryship and digital assistance
12th Week Limitations of AI tools and critical evaluation
13th Week Scenario discussions: meeting preparation, report drafts, customer correspondence
14th Week Mini project/assignment presentations (student work)
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
  • Lecture
  • Case Study
  • Presentation
Assessment Methods and Criteria
Quantity Percentage (%)
Assignment 2 40
Project 1 30
Total(%) 70
Contribution of In-term Studies to Overall Grade(%) 70
Contribution of Final Examination to Overall Grade(%) 30
Total(%) 100
ECTS Allocated Based on Student Workload
Activities Quantity Duration (Hour) Total Workload (Hour)
Midterm exam 1 1 1
Preparation for Quiz
Individual or group work 6 2 12
Preparation for Final exam 1 30 30
Course hours 14 3 42
Preparation for Midterm exam 1 20 20
Laboratory (including preparation)
Final exam 1 1 1
Homework
Project 1 15 15
Total Work Load121
Total Work Load / 30 (h)4.03
ECTS Credit of the Course4
Language of InstructionTurkish
Work Placement(s)No

Programme Qualifications / Learning Outcomes

LO1 LO2 LO3 LO4 LO5
K1
K2
K3
K4
K5
K6
K7
K8
K9
K10
K11
K12