Information Systems (Master) (Without Thesis) (English)
Master	TR-NQF-HE: Level 7	QF-EHEA: Second Cycle	EQF-LLL: Level 7

General course introduction information

Course Code:

EBIS504

Course Name:

Data Structures

Course Semester:

Fall
Spring

Course Credits:

Theoretical	Practical	Credit	ECTS
3	0	3	10

Language of instruction:

Course Requisites:

Does the Course Require Work Experience?:

Type of course:

Department Elective

Course Level:

Master

TR-NQF-HE:7. Master`s Degree

QF-EHEA:Second Cycle

EQF-LLL:7. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Öğr.Gör. HALİME SUVAY EKER

Course Lecturer(s):

Course Assistants:

Course Objective and Content

Course Objectives:

The aim of the course is to enable the students to select the most suitable data structures and algorithms for a problem by considering the existing constraints and also to evaluate the performance of the solutions they find without coding. Throughout the course, simple data structures such as sorting and searching will be explained, ranging from simple data structures to advanced data structures such as balanced trees and graphical operations.

Course Content:

Introduction to algorithms and data structures; Array data structure and dynamic memory allocation; Recursive programming; Linked lists; Stacks; Queues; Wood construction; Search techniques; Ranking techniques; Hash techniques; Information compression techniques; Basic graph algorithms; Problem-solving work.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Students will be able to design appropriate data structures and present problems in computer environment.
2) To learn basic and complex data structures and to use them in solving problems
2 - Skills
Cognitive - Practical
1) To learn how to use Data Models (such as linked list, stack, queue, tree) and data models in a software to be developed and to gain the experience of which data models can be effective for solutions to the problems.
2) Students will learn the search and sorting methods to be used in the data.
3 - Competences
Communication and Social Competence
Learning Competence
1) Students will develop skills in understanding, interpreting and evaluating existing codes.
Field Specific Competence
Competence to Work Independently and Take Responsibility

Lesson Plan

Week	Subject	Related Preparation
1)	Introduction to algorithms and data structures
2)	Linked lists
3)	Array data structure and dynamic memory allocation
4)	Recursive Programming
5)	Stacks, Queues
6)	Wood, construction
7)	Search techniques
8)	Midterm
9)	Sorting techniques
10)	Hash techniques
11)	Graph representation and algorithms: Circulation
12)	Information compression techniques
13)	Basic graph algorithms
14)	Problem-solving work.

Sources

Course Notes / Textbooks:	Data Structures and Algorithms Made Easy in Java, Narasimha Karumanchi, 2011
References:	The Algorithm Design Manual, Steven S Skiena, Springer, New York, 2012 Data Structures and Algorithms in Java, 2nd Edition, Robert Lafore, 2002

Course-Program Learning Outcome Relationship

Learning Outcomes	1	2	3	4	5
Program Outcomes

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

Program Outcomes

Level of Contribution

Learning Activity and Teaching Methods

Individual study and homework
Lesson
Group study and homework
Lab
Problem Solving
Case Study

Assessment & Grading Methods and Criteria

Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing)
Homework
Application

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Midterms	1	% 40
Final	1	% 60
total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
total		% 100

Workload and ECTS Credit Grading

Activities	Number of Activities	Workload
Course Hours	14	42
Application	4	4
Midterms	1	1
Final	1	1
Total Workload		48