1. SECOND CYCLE - MASTER'S DEGREE
  2. THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES
  3. COMPUTER ENGINEERING DEPARTMENT
  4. 1281 Computer Engineering
Course Information Course Learning Outcomes Course's Contribution To Program ECTS Workload Course Details
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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
CENG 524COMPUTATIONAL INTELLIGENCE AND ALGORITHMS3 + 01st Semester7,5

COURSE DESCRIPTION
Course Level Master's Degree
Course Type Elective
Course Objective By the end of this course, students should be able to: to understand vast amount of novel Computational Intelligence (CI) algorithms To understand grouping them into four large classes, namely, biology-, physics-, chemistry-, and mathematics-based Computational Intelligence (CI) algorithms to solve and analyze specific real-world problems
Course Content This course will be useful to multidisciplinary students including those in aeronautic engineering, mechanical engineering, industrial engineering, electrical and electronic engineering, chemical engineering, computer science, applied mathematics, physics, economy, biology, and social science, and particularly those pursuing postgraduate studies in advanced subjects. Moreover, the algorithms introduced in this course can motivate researchers to further develop more efficient and effective algorithms in dealing with many cutting-edge challenges that may sit on the periphery of their present fields of interest
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1To understand vast amount of novel Computational Intelligence (CI) algorithms
2To understand grouping them into four large classes, namely, biology-, physics-, chemistry-, and mathematics-based Computational Intelligence (CI) algorithms
3To solve and analyze specific real-world problems

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11PO 12
LO 001            
LO 002            
LO 003            
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)14570
Assignments5840
Mid-terms11515
Final examination12828
Total Work Load

ECTS Credit of the Course





195

7,5
COURSE DETAILS
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L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes