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:

EBIS503

Course Name:

Algorithm Desing And Programming

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 :

Dr.Öğr.Üyesi FERİDUN CEMAL ÖZÇAKIR

Course Lecturer(s):

Course Assistants:

Course Objective and Content

Course Objectives:	To gain knowledge and skills in basic algorithms and programming.
Course Content:	Problem solving techniques; process of input-output; algorithm analysis; precision; mathematical terms (arithmetic, relational and logical operators); conditional and cyclic idioms; vector and matrix representations; one or multi-dimensional operations other than simple data; subroutine and functions.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) To learn problem solving techniques.
2 - Skills
Cognitive - Practical
1) To solve problems through programming structures using algorithm.
3 - Competences
Communication and Social Competence
Learning Competence
1) Gain the knowledge and skills of basic algorithm.
Field Specific Competence
1) To learn the basic concepts and structures of computer programming.
Competence to Work Independently and Take Responsibility

Lesson Plan

Week	Subject	Related Preparation
1)	Computer and Programming Concepts. What is the Problem? Problem Solving Concept	Computer, Algorithm Softwares
2)	Algorithm Concept and Flow Diagrams (Flowcarts). Data Types, Constants, Variables, Arithmetic Operators	Computer, Flow Diagrams Applications
3)	Introduction to Algorithm with 5th Generation Programming Tools. Input Values in Variables, Making Arithmetic Operations with Variables and Converting Variable Contents to Output	Computer, Algorithm Application Softwares (5th Generation Programming Tools)
4)	Programming Logic, Logical Operators, Decision Structures ( IF)	Computer, Algorithm Application Software
5)	Decision Structures (SWITCH CASE)	Computer, Algorithm Application Software
6)	Loop Structures (Conditional Loop)	Computer, Algorithm Application Software
7)	Loop Structures (Loop with a Counter)	Computer, Algorithm Application Software
8)	Midterm Exam
9)	Arrays (One Dimensional)	Computer, Algorithm Application Software
10)	Arrays (Multidimensional)
11)	Sub-Programs (Subroutines) - Functions	Computer, Algorithm Application Software
12)	Sorting Algorithms	Computer, Algorithm Application Software
13)	Problem Scenarios (To Solve with Flowcarts, Pseudo Code and 5th Generation Algorithm Applications) - I	Computer, Algorithm Application Software
14)	Problem Scenarios (To Solve with Flowcarts, Pseudo Code and 5th Generation Algorithm Applications) - II	Computer, Algorithm Application Software
15)	Final Exam

Sources

Course Notes / Textbooks:	Algoritma ve Programlama Mantığı - H.Burak Tungut - Kodlab
References:	Algoritmayı Anlamak - Mustafa Eker - Nirvana Algoritmalara Giriş (Introduction To Algorithms) - Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rıvest, Clifford Stein

Course-Program Learning Outcome Relationship

Learning Outcomes	1	2	3	4
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

Peer Review
Expression
Individual study and homework
Lesson
Group study and homework
Lab
Homework
Problem Solving
Q&A / Discussion
Application (Modelling, Design, Model, Simulation, Experiment etc.)

Assessment & Grading Methods and Criteria

Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing)
Homework
Application
Individual Project
Group project
Peer Review
Case study presentation

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Attendance	42	% 5
Quizzes	4	% 15
Midterms	1	% 30
Final	1	% 50
total		% 100
PERCENTAGE OF SEMESTER WORK		% 50
PERCENTAGE OF FINAL WORK		% 50
total		% 100

Workload and ECTS Credit Grading

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Laboratory	10	1	10
Application	14	3	42
Study Hours Out of Class	10	2	20
Presentations / Seminar	2	2	4
Homework Assignments	10	1	10
Quizzes	6	1	6
Midterms	1	2	2
Final	1	2	2
Total Workload			138