1. FIRST CYCLE - BACHELOR'S DEGREE
  2. FACULTY OF ENGINEERING
  3. COMPUTER ENGINEERING DEPARTMENT
  4. 253 Computer Engineering
Course Information Course Learning Outcomes Course's Contribution To Program ECTS Workload Course Details
Print

COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
EEEN 352INTRODUCTION TO MACHINE LEARNING3 + 06th Semester5

COURSE DESCRIPTION
Course Level Bachelor's Degree
Course Type Elective
Course Objective To teach machine learning techniques, To implement these techniques in MatLab environment and to use these techniques in solving real-world problems.
Course Content Classification / Regression / Support Vector Machines / Applications
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1Knows fundamental concepts about machine learning.
2Knows machine learning structures.
3Can solve real world problem by using ML tools.
4Can make modeling and prediction by ML tools.

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11PO 12
LO 00132    2     
LO 00232    2     
LO 003  33  3   3 
LO 004    33      
Sub Total6433337   3 
Contribution211111200010

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
Mid-terms12020
Final examination12626
Total Work Load

ECTS Credit of the Course





130

5
COURSE DETAILS
 Select Year   


This course is not available in selected semester.


Print

L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes