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
SEN2212	Data Structures and Algorithms II	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 Assoc. Prof. YÜCEL BATU SALMAN RA SEVGİ CANPOLAT RA MERVE ARITÜRK
Recommended Optional Program Components:	None
Course Objectives:	The objective of this course is to analyze data structures and algorithms used in software engineering in detail. After completing the course, the student will have knowledge of applying, implementing and analysis of data structures, including, trees, binary search trees, balanced search trees, heaps and graphs. Certain fundamental techniques, such as sorting, hashing and greedy algorithms are also taught. The teaching methods of the course include lectures, practice, and project preparation.

Learning Outcomes

The students who have succeeded in this course;
The students who have succeeded in this course;
1) Describe and apply basic object oriented programming principles.
2) Implement basic data structures such as trees, binary search trees, balanced search trees, heaps and graphs.
3) Implement and use hashing algorithms.
4) Implement and use greedy algorithms.
5)Implement and use dynamic programming.
6) Choose and design data structures for writing efficient programs.

Course Content

The course content is composed of basic data structures like trees, binary search trees, balanced search trees, heaps, graphs and sorting, hashing and greedy algorithms.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction and Sorting Algorithms.	Sorting algorithms.
2)	Introduction to different tree structures.	Trees.
3)	Introduction to binary search trees.	Binary search trees.
4)	Implementing binary search tree using Java.	Binary search trees.
5)	Introduction to balanced trees and implementing AVL balanced tree structure using Java.	AVL trees.
6)	Using other balanced tree structure using Java.	Other balanced trees.
7)	Using heap structure and implementing them using Java.	Heap.
8)	Using heaps as priority queues. Midterm.	Heap.
9)	Analyzing and implementing hashing algorithms.	Hashing algorithms.
10)	Analyzing and implementing graph structure using Java.	Graph.
11)	Analyzing and implementing graph algorithms.	Graph algorithms.
12)	Analyzing and implementing greedy algorithms.	Greedy algorithms.
13)	Analyzing and implementing greedy algorithms. Quiz.	Greedy algorithms.
14)	Review.

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	% 10
Quizzes	2	% 10
Project	1	% 15
Midterms	1	% 25
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 45
PERCENTAGE OF FINAL WORK		% 55
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	2	28
Laboratory	14	3	42
Project	1	30	30
Quizzes	2	15	30
Midterms	1	20	20
Final	1	25	25
Total Workload			175

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 and science.
2)	Adequate knowledge in subjects specific to Computer Engineering.
3)	Ability to use theoretical and practical knowledge in Computer Engineering subjects for complex engineering problems.
4)	Ability to identify, define, and formulate complex engineering problems
5)	Ability to select and apply appropriate analysis and modeling methods to solve complex engineering problems.
6)	Ability to design a complex system, process, device, or product under realistic constraints and conditions to meet specific requirements, and to apply modern design methods for this purpose
7)	Ability to develop, select, and use modern techniques and tools required for the analysis and solution of complex problems encountered in computer engineering applications.
8)	Ability to use information technologies effectively
9)	Ability to design experiments for the investigation of complex engineering problems or research topics in computer engineering.
10)	Ability to conduct experiments, collect data, analyze and interpret results for the investigation of complex engineering problems or research topics in computer engineering
11)	Ability to work effectively in intra-disciplinary teams.
12)	Ability to work effectively in multidisciplinary teams.
13)	Ability to work independently.
14)	Ability to communicate effectively in both oral and written forms
15)	Knowledge of at least one foreign language
16)	Ability to write effective reports, understand written reports, and prepare design and production reports.
17)	Ability to deliver effective presentations and to give and receive clear and understandable instructions.
18)	Awareness of the necessity of lifelong learning
19)	Ability to access information, follow developments in science and technology, and continuously improve oneself.
20)	Ability to be aware of professional and ethical responsibilities and to act in accordance with ethical principles.
21)	Knowledge of standards used in engineering applications.
22)	Knowledge of professional practices in business life such as project management, risk management, and change management.
23)	Awareness of entrepreneurship and innovation.
24)	Knowledge of sustainable development.
25)	Knowledge of the impacts of engineering applications on health, environment, and safety in universal and societal dimensions, as well as awareness of contemporary issues reflected in the field of engineering.
26)	Awareness of the legal consequences of engineering solutions.