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
SEN2211	Data Structures and Algorithms I	Spring	2	2	3	7

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 :	Dr. Öğr. Üyesi BETÜL ERDOĞDU ŞAKAR
Course Lecturer(s):	Dr. Öğr. Üyesi BETÜL ERDOĞDU ŞAKAR RA MERVE ARITÜRK Prof. Dr. NAFİZ ARICA Instructor DUYGU ÇAKIR YENİDOĞAN RA SEVGİ CANPOLAT
Recommended Optional Program Components:	None
Course Objectives:	This is an introductory course on common data structures that are used in software engineering. After completing the course, the student will have knowledge of applying, implementing and analysis of basic data structures, including, lists, stacks and queues. Certain fundamental techniques, such as sorting, searching and recursion are also taught.

Learning Outcomes

The students who have succeeded in this course;
1) Describe and apply basic object oriented programming principles.
2) Implement basic data structures such as linked lists, stacks and queues.
3) Analyze the complexity and efficiency of algorithms.
4) Choose and design data structures for writing efficient programs.
5) Implement recursive algorithms.
6) Describe and implement sorting algorithms on common data structures.
7) Describe and implement search algorithms on common data structures.

Course Content

The course content is composed of object oriented Java review, the complexity and efficiency of algorithms, introduction to list-stack-queue structures, implementing list-stack-queue structures, recursion, searching algorithms and sorting algorithms.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction to Data Structures and Algorithms Complexity Analysis
2)	Introduction to Linked Lists
3)	Doubly Linked Lists Ordered Linked Lists
4)
5)	Stacks
6)	Stacks for Algebraic Operations
7)	Queues
8)	Queues
9)	Data Structure Classes in Java
10)	Recursion
11)	Recursive Complexity
12)	Searching Algorithms
13)	Sorting Algorithms
14)	Sorting algorithms

Sources

Course Notes / Textbooks:	Data Structures & Problem Solving Using Java (Mark Allen Weiss) Data Structures and Algorithm Analysis in Java (Mark Allen Weiss) Data Structures and Abstractions with Java (Frank Carrano)
References:	Yok

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Laboratory	4	% 20
Quizzes	5	% 20
Midterms	1	% 20
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 40
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Workload
Course Hours	14	28
Laboratory	14	28
Study Hours Out of Class	12	24
Midterms	10	52
Final	5	32
Total Workload		164

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.