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
GEP0640	Towards Zero Hunger (SDG 2)	Fall Spring	3	0	3	5

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:	GE-Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Hybrid
Course Coordinator :	Assist. Prof. MÜGE KESİCİ
Recommended Optional Program Components:	Yok
Course Objectives:	The aim of this course is to present the developmental stages of agriculture through human history and the projection into the future. In addition, it is to ensure that they have information about how today's technologies and possible future scenarios will affect and direct agriculture. At the end of the course, students will design the agriculture of the future with the knowledge they have acquired.

Learning Outcomes

The students who have succeeded in this course;
1. Gain information about agriculture history.
2. Comprehend the contribution of food safety to the world development.
3. Learn about poverty.
4. Learn examples in food right.
5. Understand the relationship between agriculture and food security.
6. Gain knowledge about sustainable agriculture.
7. Learn European Green Deal, green transition and etc.
8. Have foresight about the effect of global climate change on food safety.

Course Content

Students who responsible the course are expected to follow the course in MSTeams during the course hours.
Students who have questions can have either an online or a face-to-face meeting with the instructor during the office hours.
The teaching method of the course is lecture. Project assignments (in the form of a case study) given at the beginning of the semester will be given to students individually as oral presentations in the last two weeks of the semester.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction to the course	yok
2)	Brief history of agriculture and revolutions	yok
3)	What is F2F strategy?	yok
4)	World hunger and poverty	yok
5)	Agricultural production systems	yok
6)	Transition to sustainable agriculture	yok
7)	Paradigm for zero hunger	yok
8)	Mid term exam
9)	Food security	yok
10)	Global climate change effect on agriculture	yok
11)	Technology impact to achieve zero hunger	yok
12)	European green deal	yok
13)	Student assignment presentations	yok
14)	Student assignment presentations	yok

Sources

Course Notes / Textbooks:	FAO, The Future of Food and Agriculture: Trends and Challenges, 2017. Scientific papers
References:	FAO, The Future of Food and Agriculture: Trends and Challenges, 2017. Scientific papers

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Attendance	14	% 0
Presentation	1	% 20
Midterms	1	% 30
Final	1	% 50
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 50
PERCENTAGE OF FINAL WORK		% 50
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	13	3	39
Study Hours Out of Class	12	4	48
Presentations / Seminar	2	10	20
Homework Assignments	1	10	10
Midterms	1	2	2
Final	1	2	2
Total Workload			121

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)	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.
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.	4
9)	Learn about business life practices such as project management, risk management, and change management; develop an awareness of entrepreneurship, innovation, and sustainable development.	3
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.	4
11)	Cooperate efficiently in intra-disciplinary and multi-disciplinary teams; and show self-reliance when working on Artificial Intelligence-related problems.	4