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
ELT5887	Seminar	Spring	0	0	0	10

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:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Prerequisites:	ELT5888-1 - Thesis
Mode of Delivery:	Face to face
Course Coordinator :
Course Lecturer(s):	Dr. Öğr. Üyesi ENİSA MEDE Prof. Dr. KENAN DİKİLİTAŞ
Recommended Optional Program Components:	None
Course Objectives:	Graduate Seminar course is a systematic study that prepares students for their thesis writing. To help students conduct a thesis study, the course involves augmenting critical thinking, researching, and academic writing skills.

Learning Outcomes

The students who have succeeded in this course;
1. Critique research articles on current topics
2. Formulate a specific research topic and research questions
3. Conduct literature review relevant to a research topic they have selected
4. Collaborate with faculty to develop applicable research methodology for data collection and analyses
5. Write a research proposal outlining key elements of the proposed project and present it orally in seminar

Course Content

The seminar course introduces students with various current research ideas widening their perspectives and awareness of topics of interests through invited speakers and their presentations. The course orients students to conduct literature review on a pre-determined subject, to help them gain competence in synthesizing the literature, collect data, analyze, interpret and discuss the findings.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction to the seminar course	Syllabus
2)	Academic study aim, academic writing, and plagiarism	Reading articles
3)	Identifying a research problem and writing research questions	Reading related book chapters and articles
4)	Literature review	Reading articles
5)	Data collection methods: Quantitative	Inviting a guest speaker for a seminar
6)	Data collection methods: Qualitative	Inviting a guest speaker for a seminar
7)	Data analysis	Reading articles
8)	Discussion based on the findings	Reading articles
9)	Discussion and conclusion
10)	Feedback on projects
11)	Feedback on projects
12)	Project presentations
13)	Project presentations
14)	Project presentations

Sources

Course Notes / Textbooks:	The instructor may assign readings, handouts, web-based activities throughout the semester.
References:	American Psychological Association. (2009). Publication manual of the American psychological association (6th edition). Washington, DC: Author. (or other appropriate style manual)

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Attendance	2	% 10
Homework Assignments	5	% 50
Project	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 40
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	10	14	140
Presentations / Seminar	1	1	1
Project	1	10	10
Homework Assignments	5	19	95
Total Workload			246

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)	Have sufficient background in mathematics, science and artificial intelligence engineering.
2)	Use theoretical and applied knowledge in the fields of mathematics, science and artificial intelligence engineering together for engineering solutions.
3)	Identify, define, formulate and solve engineering problems, select and apply appropriate analytical methods and modeling techniques for this purpose.
4)	Analyse a system, system component or process and design it under realistic constraints to meet desired requirements; apply modern design methods in this direction.
5)	Select and use modern techniques and tools necessary for engineering applications.
6)	Design and conduct experiments, collect data, and analyse and interpret results.
7)	Work effectively both as an individual and as a multi-disciplinary team member.
8)	Access information via conducting literature research, using databases and other resources
9)	Follow the developments in science and technology and constantly update themself with an awareness of the necessity of lifelong learning.
10)	Use information and communication technologies together with computer software with at least the European Computer License Advanced Level required by their field.
11)	Communicate effectively, both verbal and written; know a foreign language at least at the European Language Portfolio B1 General Level.
12)	Have an awareness of the universal and social impacts of engineering solutions and applications; know about entrepreneurship and innovation; and have an awareness of the problems of the age.
13)	Have a sense of professional and ethical responsibility.
14)	Have an awareness of project management, workplace practices, employee health, environment and work safety; know the legal consequences of engineering practices.