ALGORITHM ANALYSIS PROGRAMME COURSE DESCRIPTION

Code	Name of the Course Unit	Semester	In-Class Hours (T+P)	Credit	ECTS Credit
YZM201	ALGORITHM ANALYSIS	3	4	3	5

GENERAL INFORMATION
Language of Instruction :	Turkish
Level of the Course Unit :	BACHELOR'S DEGREE, TYY: + 6.Level, EQF-LLL: 6.Level, QF-EHEA: First Cycle
Type of the Course :	Compulsory
Mode of Delivery of the Course Unit	-
Coordinator of the Course Unit	Assist.Prof. SERKAN GÖNEN
Instructor(s) of the Course Unit	Assist.Prof. ABDULLAH SEVİN
Course Prerequisite	No

OBJECTIVES AND CONTENTS
Objectives of the Course Unit:	Algorithms play a central role in science and computer applications. Algorithm Analysis and Design Computer Science is one of the most fundamental courses in the computer science curriculum. The two main goals of this course are to introduce students to the basic concepts of algorithm analysis and to ensure that students understand the importance of algorithm efficiency. Students are equipped with the knowledge and skills to effectively perform analysis of new algorithms. To teach algorithm design techniques. These techniques will provide students with the necessary tools to design algorithms for new problems. The algorithm analysis and design process will be classified and analyzed with known algorithms. In addition, many new algorithms will be discussed.
Contents of the Course Unit:	Introduction, algorithm analysis, algorithm design, overview of NP-hard problems

KEY LEARNING OUTCOMES OF THE COURSE UNIT (On successful completion of this course unit, students/learners will or will be able to)
Students taking this course will be able to; Understand algorithm efficiency and its importance
Analyze the time and space utilization adequacy of algorithms and programs in the worst, best, and average cases
Discuss various problem-solving techniques and their applications
Understand the reasons for using an algorithmic approach and demonstrate the necessary knowledge
Gain awareness of uncertain and difficult problems, NP-definite problems, similar theoretical concepts, and approach development
Design an algorithm and programming solution for an engineering problem

WEEKLY COURSE CONTENTS AND STUDY MATERIALS FOR PRELIMINARY & FURTHER STUDY
Week	Preparatory	Topics(Subjects)	Method
1	-	Mathematical repetition	Explanation, Question-Answer, Problem-Solving Method
2	-	Fundamentals of Analysis 1	Explanation, Question-Answer, Problem-Solving Method
3	-	Fundamentals of Analysis 2-Non-recursive algorithms	Explanation, Question-Answer, Problem-Solving Method
4	-	Counting analysis, Sequences, and repetition relations	Explanation, Question-Answer, Problem-Solving Method
5	-	Solution of repetitive relations 1	Explanation, Question-Answer, Problem-Solving Method
6	-	Analysis of Recursive Algorithms	Explanation, Question-Answer, Problem-Solving Method
7	-	Introduction to Design	Explanation, Question-Answer, Problem-Solving Method
8	-	MID-TERM EXAM	-
9	-	Introduction to Design	Explanation, Question-Answer, Problem-Solving Method
10	-	Greedy Algorithms	Explanation, Question-Answer, Problem-Solving Method
11	-	Dynamic Programming Algorithms	Explanation, Question-Answer, Problem-Solving Method
12	-	Exception Handling	Explanation, Question-Answer, Problem-Solving Method
13	-	Introduction to NP and NP-complete problems, understanding, backtracking method	Explanation, Question-Answer, Problem-Solving Method
14	-	Approximation algorithms for NP problems	Explanation, Question-Answer, Problem-Solving Method
15	-	General Review	Explanation, Question-Answer, Problem-Solving Method
16	-	FINAL EXAM	-
17	-	FINAL EXAM	-

SOURCE MATERIALS & RECOMMENDED READING
Robert Sedgewick, Algorithms in C, Parts 1-4 Introduction to Algorithms, Charles E. Cormen, Thomas H.; Leiserson

ASSESSMENT
Assessment & Grading of In-Term Activities	Number of Activities	Degree of Contribution (%)	Description

Level of Contribution
0	1	2	3	4	5

KNOWLEDGE
Theoretical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Ability to identify, analyze, design, model and solve complex engineering problems based on engineering, science and mathematics fundamentals						5

KNOWLEDGE
Factual
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Ability to apply engineering design to produce solutions that meet specific needs, taking into account global, cultural, social, environmental and economic factors as well as public health, safety and well-being					4

SKILLS
Cognitive
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Ability to communicate effectively with various stakeholders					4

SKILLS
Practical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	The ability to recognize ethical and professional responsibilities in engineering and make informed decisions considering the impact of engineering solutions in their global, economic, environmental and social contexts						5

OCCUPATIONAL
Autonomy & Responsibility
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	The ability to recognize ethical and professional responsibilities in engineering and make informed decisions considering the impact of engineering solutions in their global, economic, environmental and social contexts					4

OCCUPATIONAL
Learning to Learn
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Ability to acquire new knowledge and find ways to apply it when necessary, using appropriate learning strategies				3

OCCUPATIONAL
Communication & Social
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Ability to work effectively in a team where its members lead together, create a collaborative and inclusive environment, set goals, plan tasks, and meet goals				3

OCCUPATIONAL
Occupational and/or Vocational
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Ability to design and conduct appropriate experiments, analyze and interpret data, and apply engineering principles to draw conclusions					4

WORKLOAD & ECTS CREDITS OF THE COURSE UNIT
Workload for Learning & Teaching Activities
Type of the Learning Activites	Learning Activities (# of week)	Duration (hours, h)	Workload (h)
Lecture & In-Class Activities	14	4	56
Preliminary & Further Study	14	5	70
Land Surveying	0	0	0
Group Work	0	0	0
Laboratory	0	0	0
Reading	0	0	0
Assignment (Homework)	0	0	0
Project Work	0	0	0
Seminar	0	0	0
Internship	0	0	0
Technical Visit	0	0	0
Web Based Learning	0	0	0
Implementation/Application/Practice	0	0	0
Practice at a workplace	0	0	0
Occupational Activity	0	0	0
Social Activity	0	0	0
Thesis Work	0	0	0
Field Study	0	0	0
Report Writing	0	0	0
Final Exam	1	2	2
Preparation for the Final Exam	1	1	1
Mid-Term Exam	1	1	1
Preparation for the Mid-Term Exam	1	1	1
Short Exam	2	1	2
Preparation for the Short Exam	0	0	0
TOTAL	34	0	133