1. FIRST CYCLE - BACHELOR'S DEGREE
  2. FACULTY OF ENGINEERING
  3. INDUSTRIAL ENGINEERING DEPARTMENT
  4. 255 Industrial 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
YBS 483ARTIFICIAL INTELLIGENCE APPLICATIONS3 + 05th Semester5

COURSE DESCRIPTION
Course Level Bachelor's Degree
Course Type Elective
Course Objective Artificial Intelligence aims to solve real-life learning, inference, optimization, prediction, classification and recognition problems.
Course Content Artificial intelligence languages will be explained and AI based programs will be made with modern programming languages (python, C #, matlab). These are Artificial Intelligence Problems, Machine Learning and Detection, Expert Systems, Image Processing, Optimization, Artificial Neural Networks and Genetic Algorithms, Natural Language Processing, Robotics Applications.
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1To gain the ability to solve real life learning, inference, optimization, estimation, classification and recognition problems with artificial intelligence.
2To gain the ability to apply the basic concepts, techniques, mathematics and software infrastructure of Artificial Intelligence.
3To gain the ability to develop intelligent software
4To acquire the ability to recognize and use artificial intelligence languages and tools such as Python, matlab.

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11PO 12PO 13
LO 001             
LO 002             
LO 003             
LO 004             
Sub Total             
Contribution0000000000000

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Assignments4624
Mid-terms11010
Final examination11414
Presentation / Seminar Preparation11414
Report / Project12626
Total Work Load

ECTS Credit of the Course





130

5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2023-2024 Fall1CAN BERK KALAYCI


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Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
YBS 483 ARTIFICIAL INTELLIGENCE APPLICATIONS 3 + 0 1 Turkish 2023-2024 Fall
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Assoc. Prof. Dr. CAN BERK KALAYCI cbkalayci@pau.edu.tr MUH A0425 %70
Goals Artificial Intelligence aims to solve real-life learning, inference, optimization, prediction, classification and recognition problems.
Content Artificial intelligence languages will be explained and AI based programs will be made with modern programming languages (python, C #, matlab). These are Artificial Intelligence Problems, Machine Learning and Detection, Expert Systems, Image Processing, Optimization, Artificial Neural Networks and Genetic Algorithms, Natural Language Processing, Robotics Applications.
Topics
WeeksTopics
1 Introduction to python basics and setup
2 Scientific computing with Python
3 Vectors, matrices and multidimensional arrays with Numpy
4 Plotting and Visualization with Matplotlib
5 Machine Learning: Regression
6 Machine Learning: Classification
7 Machine Learning: Clustering
8 Computational Intelligence and heuristic algorithms
9 Genetic Algorithms
10 Applications of artificial intelligence
11 Applications of artificial intelligence
12 Applications of artificial intelligence
13 Applications of artificial intelligence
14 Project presentations
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