ARTIFICIAL INTELLIGENCE ENGINEERING
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
COP3342	Prompt Engineering	Spring	3	0	3	6

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Assist. Prof. FATİH KAHRAMAN
Recommended Optional Program Components:	-
Course Objectives:	This course is designed to provide a comprehensive understanding of prompt engineering with a focus on the Generative Pretrained Transformer 4 (GPT-4o) and its application, ChatGPT. The curriculum is tailored for a diverse range of students, regardless of their coding ability, aiming to bridge the gap between technical AI knowledge and practical everyday use cases. The aim is to empower students to utilize AI tools like ChatGPT for various tasks such as content creation, business productivity, media production, and more. By the end of the course, students will not only have a sound understanding of AI and prompt engineering but also hands-on experience in using AI tools for solving real-world problems, potentially opening up new career opportunities in the field.

Learning Outcomes

The students who have succeeded in this course;
A student who successfully completes this course will:

1) Understand the fundamental concepts of AI and GPT-4.
2) Apply prompt engineering strategies.
3) Utilize AI tools for various tasks such as content creation, business productivity, and media production.
4) Benefit from automation and workflow optimization tools for efficient work processes.
5) Comprehend the potential of AI in career development and understand the use of AI tools in different fields.

Course Content

This course is a comprehensive exploration of prompt engineering, focusing on AI technologies like GPT-4 and ChatGPT, offering students from all fields the knowledge to simplify complex information and solve problems using AI. It also emphasizes practical applications of these technologies in content creation, business, media production, and career development, regardless of the students' coding abilities.

This course will be conducted through theoretical lectures, hands-on exercises, project-based learning, group discussions, and practical applications based on real-world scenarios.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction to AI and GPT-4	-
2)	Exploring ChatGPT
3)	Introduction to Prompt Engineering
4)	Hands-on Session with ChatGPT
5)	Enhancing ChatGPT
6)	Diving Deeper into Prompt Engineering
7)	Extending Capabilities
8)	Mid-course Project & Review
9)	AI in Business and Marketing
10)	Automations and Workflow Optimizations
11)	AI in Media Production
12)	Exploring Career Opportunities with AI

Sources

Course Notes / Textbooks:	Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach (4th Edition). Pearson. Domingos, P. (2018). The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World. Basic Books. Bostrom, N. (2016). Superintelligence: Paths, Dangers, Strategies. Oxford University Press.
References:	Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach (4th Edition). Pearson. Domingos, P. (2018). The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World. Basic Books. Bostrom, N. (2016). Superintelligence: Paths, Dangers, Strategies. Oxford University Press.

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Total		%
PERCENTAGE OF SEMESTER WORK		% 0
PERCENTAGE OF FINAL WORK		%
Total		%

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Build up a body of knowledge in mathematics, science and Artificial Intelligence Engineering subjects; use theoretical and applied information in these areas to model and solve complex engineering problems.
2)	Design complex Artificial Intelligence systems, platforms, processes, devices or products under realistic constraints and conditions, in such a way as to meet the desired result; apply modern design methods for this purpose.	3
3)	Identify, formulate, and solve complex Artificial Intelligence Engineering problems; select and apply proper modeling and analysis methods for this purpose.
4)	Devise, select, and use modern techniques and tools needed for solving complex problems in Artificial Intelligence Engineering practice; employ information technologies effectively.
5)	Design and conduct numerical or physical experiments, collect data, analyze and interpret results for investigating the complex problems specific to Artificial Intelligence Engineering.
6)	Ability to communicate effectively in English and Turkish (if he/she is a Turkish citizen), both orally and in writing. Write and understand reports, prepare design and production reports, deliver effective presentations, give and receive clear and understandable instructions.	4
7)	Recognize the need for life-long learning; show ability to access information, to follow developments in science and technology, and to continuously educate oneself.
8)	Develop an awareness of professional and ethical responsibility, and behave accordingly. Be informed about the standards used in Artificial Intelligence Engineering applications.
9)	Learn about business life practices such as project management, risk management, and change management; develop an awareness of entrepreneurship, innovation, and sustainable development.
10)	Acquire knowledge about the effects of practices of Artificial Intelligence Engineering on health, environment, security in universal and social scope, and the contemporary problems of Artificial Intelligence Engineering; is aware of the legal consequences of Mechatronics engineering solutions.
11)	Cooperate efficiently in intra-disciplinary and multi-disciplinary teams; and show self-reliance when working on Artificial Intelligence-related problems.