Computer Engineering

Course Code	Course Name	Year	Period	Semester	T+A+L	Credit	ECTS
05050002	Analysis of Algorithms	3	Autumn	5	3+0+0	3	5

Course Type	Compulsory
Course Cycle	Bachelor's (First Cycle) (TQF-HE: Level 6 / QF-EHEA: Level 1 / EQF-LLL: Level 6)
Course Language	Turkish
Methods and Techniques	-
Mode of Delivery	Face to Face
Prerequisites	-
Coordinator	-
Instructor(s)	Asst. Prof. Ali Osman ÇIBIKDİKEN
Instructor Assistant(s)	-

Name and Surname	Room	E-Mail Address	Internal	Meeting Hours
Asst. Prof. Ali Osman ÇIBIKDİKEN	A-1KAT	[email protected]	0

Basic Vocational Courses
Specialization / Field Courses	X
Support Courses	X
Transferable Skills Courses
Humanities, Communication and Management Skills Courses

Relationship Levels
Lowest	Low	Medium	High	Highest
1	2	3	4	5

#	Program Learning Outcomes	Level
P2	Ability to identify, formulate, and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose	5
P3	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
P8	Awareness of the necessity of lifelong learning; ability to access information, to follow developments in science and technology and to renew himself continuously	3

Upon the successful completion of this course, students will be able to:
No	Learning Outcomes	Outcome Relationship	Measurement Method **
O1	Knowledge of algorithm design and analysis techniques.	P.2.5	1
O2	Algorithm development knowledge and creation of appropriate data structure for the algorithm.	P.2.15	1,7
O3	Identifying learning needs and guiding the learning process.	P.2.16	1
O4	Identifying learning resources and accessing them effectively and quickly.	P.2.17	1
O5	To gain lifelong learning knowledge.	P.8.10	1
O6	Ability to criticize acquired knowledge and skills	P.8.11	1
O7	Ability to use information and communication technologies in the design process	P.3.13	1
** Written Exam: 1, Oral Exam: 2, Homework: 3, Lab./Exam: 4, Seminar/Presentation: 5, Term Paper: 6, Application: 7

Week	Topics
1	Introduction. Some representative problems.
2	Basics of algorithm analysis.
3	Graphs
4	Greedy algorithms-I
5	Greedy algorithms-II
6	Midterm
7	Divide and conquer-I
8	Divide and conquer-II
9	Dynamic programming
10	Network Flow-I
11	Network Flow-II
12	NP and computational intractability-I
13	NP and computational intractability-II

Resources

Introduction to Algorithms, 2nd Ed. by. Cormen, Leiserson, Rivest & Stein, MIT Press, (2001)

In-Term Studies	Quantity	Percentage
Attendance	-	-
Laboratory	-	-
Practice	-	-
Course Specific Internship (If Any)	-	-
Homework	-	-
Presentation	-	-
Projects	-	-
Quiz	-	-
Midterms	1	40 (%)
Final Exam	1	60 (%)
Total		100 (%)

	Quantity	Duration	Total Work Load
Course Week Number and Time	14	3	42
Out-of-Class Study Time (Pre-study, Library, Reinforcement)	14	3	42
Midterms	1	30	30
Quiz	0	0	0
Homework	0	0	0
Practice	0	0	0
Laboratory	0	0	0
Project	0	0	0
Workshop	0	0	0
Presentation/Seminar Preparation	0	0	0
Fieldwork	0	0	0
Final Exam	1	36	36
Other	0	0	0
Total Work Load:			150
Total Work Load / 30			5
Course ECTS Credits:			5

Relationship Levels
Lowest	Low	Medium	High	Highest
1	2	3	4	5

#	Learning Outcomes	P2	P3	P8
O1	Knowledge of algorithm design and analysis techniques.	4	2	1
O2	Algorithm development knowledge and creation of appropriate data structure for the algorithm.	3	1	4
O3	Identifying learning needs and guiding the learning process.	2	4	3
O4	Identifying learning resources and accessing them effectively and quickly.	5	1	5
O5	Ability to use information and communication technologies in the design process	1	3	3
O6	To gain lifelong learning knowledge.	2	1	5
O7	Ability to criticize acquired knowledge and skills	3	1	4