COMPUTER 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 :	Assist. Prof. ÖZGE YÜCEL KASAP
Course Lecturer(s):	Assist. Prof. BETÜL ERDOĞDU ŞAKAR RA MERVE ARITÜRK Prof. Dr. NAFİZ ARICA Assist. Prof. 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. The teaching methods of the course are lecture and practice.

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	2	% 25
Quizzes	2	% 15
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	Duration (Hours)	Workload
Course Hours	14	2	28
Laboratory	14	2	28
Homework Assignments	1	8	8
Quizzes	2	20	40
Midterms	1	30	30
Final	1	30	30
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)	Adequate knowledge in mathematics, science and computer engineering; the ability to use theoretical and practical knowledge in these areas in complex engineering problems.
2)	Ability to identify, formulate, and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose.
3)	Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions; ability to apply modern design methods for this purpose.
4)	Ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in computer engineering applications; ability to use information technologies effectively.
5)	Ability to design, conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or computer engineering research topics.
6)	Ability to work effectively within and multi-disciplinary teams; individual study skills.
7)	Ability to communicate effectively in verbal and written Turkish; knowledge of at least one foreign language; ability to write active reports and understand written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8)	Awareness of the necessity of lifelong learning; ability to access information, to follow developments in science and technology and to renew continuously.	3
9)	To act in accordance with ethical principles, professional and ethical responsibility; information on the standards used in engineering applications.
10)	Information on business practices such as project management, risk management and change management; awareness of entrepreneurship and innovation; information about sustainable development.	4
11)	Knowledge of the effects of engineering practices on health, environment and safety in the universal and social scale and the problems of the era reflected in engineering; awareness of the legal consequences of engineering solutions.