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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
ELK 521OPTIMIZATION TECHNIQUES3 + 02nd Semester7,5

COURSE DESCRIPTION
Course Level Doctorate Degree
Course Type Elective
Course Objective To teach Fundamentals related to optimization techniques and to gain graduate students the ability of using these techniques in solving real world problems.
Course Content One-dimensional nonlinear numerical optimization / Multi-dimensional nonlinear numerical optimization / Mathematical background / Analytical conditions for optimality / First-order methods / Second-order methods / Second-order approximate methods / Applications
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1Knows the fundamental concepts of numerical optimization
2Knows gradient-based unconstrained numerical optimization methods
3Can solve related real-world problems by optimization methods
4Can do modeling and prediction by Artificial Neural Networks

COURSE'S CONTRIBUTION TO PROGRAM
Data not found.

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)14228
Assignments51260
Mid-terms13535
Final examination13030
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