GENERATIVE ARTIFICIAL INTELLIGENCE APPLICATIONS

SBMO134

Course Code: SBMO134
Semester: -
Theory+Practice: 3 + 0
ECTS: 4

Course Type

Elective Course

Course Level

Associate Degree

Year of Study

Semester

ECTS

Name of Lecturer(s)

Learning Outcomes

At the end of this course, the students;

Identifies the functions, limitations, and applications of generative AI.technologies.
Explains the contributions of AI tools in office management.
Understands AI applications in the context of digital literacy and 21st-century skills.
Distinguishes the role of AI tools in virtual secretaryship and digital assistance.
Explains data privacy, copyright, and ethical principles; develops awareness of responsible use.

Mode of Delivery

Face to face

Prerequisites

Recommended Optional Programme Components

Course Description

This 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
1^st Week	Introduction to the course, objectives, and scope. General framework of digital transformation and AI concepts
2^nd Week	21st-century skills and digital literacy. Changing roles in office environments
3^rd Week	Introduction to generative AI: basic concepts, mechanisms, opportunities, and limitations
4^th Week	Types of AI tools: text, visual, audio, presentation generation
5^th Week	Text generation in office management: email drafts, official documents, note-taking
6^th Week	AI support in presentation and content design. Introduction to visual generation tools
7^th Week	Meeting planning, task management, and AI-assisted digital secretaryship
8^th Week	Midterm exam
9^th Week	Ethical principles in AI use: transparency, responsibility, copyright, plagiarism
10^th Week	Data privacy and security: protection of personal data, institutional risks
11^th Week	Future job roles in virtual secretaryship and digital assistance
12^th Week	Limitations of AI tools and critical evaluation
13^th Week	Scenario discussions: meeting preparation, report drafts, customer correspondence
14^th 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 Load			121
Total Work Load / 30 (h)			4.03
ECTS Credit of the Course			4

Language of Instruction

Turkish

Work Placement(s)

Programme Qualifications / Learning Outcomes

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