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
SEN1002	Object Oriented Programming (Java)	Spring	2	2	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:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Assist. Prof. DERYA BODUR
Course Lecturer(s):	Assist. Prof. TAMER UÇAR Assist. Prof. DUYGU ÇAKIR YENİDOĞAN RA MERVE ARITÜRK RA SEVGİ CANPOLAT
Recommended Optional Program Components:	The teaching methods of the course include lectures, and practice.
Course Objectives:	The aim of this course is to intoduce the Java language and object oriented programming techniques to the students. The main topics covered in this course are inheritance and polymorphism, gui interfaces, exception handling, file operations, recursive methods, search and sorting algorithms and generic types.

Learning Outcomes

The students who have succeeded in this course;
1. Develops the inheritance technique in class design.
2. Applies the concept of polymorphism
3. Create graphical user interface components and control events.
4. Develop programs with exception handling.
5. Define the String class and regular expressions.
6. Develops programs that write and read text and serialized objects files.
7. Builds and implements Enum types.
8. Create recursive methods.
9. Define sorting and search algorithms.

Course Content

1. Inheritance
2. Polymorphism
3. GUI interface design
4. String operations and regular expressions
5. Exception handling
6. File operations
7. Using Enumeration
8. Recursive methods
9. Search and sort algorithms
10. Generic types

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Classes and Objects
1)
2)	Inheritance
3)	Polymorphism
4)	Polymorphism
5)	GUI Components
6)	GUI and Event-driven Programming
7)	Case Study: Object Oriented Design with the UML
8)	Strings, Characters and Regular Expressions
9)	Exception Handling
11)	Files and Streams, object serialization
12)	Recursion
13)	Searching, Sorting (Selection Sort, Merge, Insertion Sort)
14)	Generic Classes and Methods

Sources

Course Notes / Textbooks:	Paul Deitel, Harvey Deitel, Java: How to Program, Pearson, ISBN-10: 0132575663
References:	C. Thomas Wu, An Introduction to Object Oriented Programming with Java, McGraw Hill. Y. Daniel Liang, Introduction to Java Programming, Comprehensive, Pearson.

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Quizzes	2	% 30
Midterms	1	% 30
Final	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	14	2	28
Laboratory	14	2	28
Study Hours Out of Class	14	3	42
Quizzes	2	2	4
Midterms	1	12	12
Final	1	15	15
Total Workload			129

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.	3
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.	4
11)	Cooperate efficiently in intra-disciplinary and multi-disciplinary teams; and show self-reliance when working on Artificial Intelligence-related problems.