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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
YOBS 527ALGORITHM DESIGN AND ANALYSIS3 + 02nd Semester7,5

COURSE DESCRIPTION
Course Level Master's Degree
Course Type Elective
Course Objective The aim of this course is to help students develop algorithmic intuition
Course Content divide and conquer, brute force, decreas and conquer, transform and conquer, dynamic programming, greedy programming, iteratie improvement ve NP completeness
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1Explains basics of algorithm analysis
2Explains algorithm analysis techniques
3Explains dynamic programming
4Explains greedy algorithm technique

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11PO 12
LO 001            
LO 002            
LO 003            
LO 004            
Sub Total            
Contribution000000000000

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Hours for off-the-classroom study (Pre-study, practice)14342
Assignments24080
Mid-terms11313
Final examination11818
Total Work Load

ECTS Credit of the Course






195

7,5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2020-2021 Fall1ELİF HAYTAOĞLU


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Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
YOBS 527 ALGORITHM DESIGN AND ANALYSIS 3 + 0 1 Turkish 2020-2021 Fall
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Asts. Prof. Dr. ELİF HAYTAOĞLU eacar@pau.edu.tr MUH A0250 %70
Goals The aim of this course is to help students develop algorithmic intuition
Content divide and conquer, brute force, decreas and conquer, transform and conquer, dynamic programming, greedy programming, iteratie improvement ve NP completeness
Topics
WeeksTopics
1 Introlduction
2 Datastructures Overview
3 Algorithm Analysis Fundamentals
4 Algorithm Analysis Fundamentals
5 Brute Force
6 Brute Force
7 Decrease Conquer
8 Decrease Conquer
9 Divide Conquer
10 Transform Conquer
11 Midterm
12 Dynamic Programming
13 Branch Bound
14 Backtracking
Materials
Materials are not specified.
Resources
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam50Final Exam
Midterm Exam50Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes