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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
YBS 442INTELLIGENT SYSTEMS2 + 15th Semester5

COURSE DESCRIPTION
Course Level Bachelor's Degree
Course Type Elective
Course Objective To gain the ability to design and implement a Smart System, to develop an Intelligent System, and to study how to combine and integrate Artificial Intelligence topics in depth and breadth.
Course Content Introduction to Intelligent Systems, Artificial Neural Networks, Evolutionary Computation, Fuzzy Logic, Expert Systems, Hybrid Intelligent Systems, Fuzzy Expert systems, Neural Expert Systems, Neuro-fuzzy Systems, Evolutionary Neural Networks.
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1To be able to design and implement own IS system
2To learn ability to use and integrate Software Tools in Artificial Neural Networks, Genetic Algorithms, Fuzzy Logic, Expert Systems.
3 To learn basic concepts of Intelligent Systems, mathematical and software background; to have ability to apply Intelligent Systems to problems. To have both a general “breadth” knowledge of AI techniques, plus a deeper specialized knowledge of one particular sub-area within AI; how to combine or integrate them.

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11PO 12
LO 001121542232545
LO 002      545235
LO 003      444445
Sub Total121542111111111115
Contribution010211444445

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)14456
Mid-terms11515
Final examination11717
Total Work Load

ECTS Credit of the Course






130

5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2020-2021 Spring1HAMİD YEŞİLYAYLA
Details 2019-2020 Spring1HAMİD YEŞİLYAYLA


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Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
YBS 442 INTELLIGENT SYSTEMS 2 + 1 1 Turkish 2020-2021 Spring
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Lecturer HAMİD YEŞİLYAYLA hyesilyayla@pau.edu.tr İİBF AB111 İİBF C0304 %70
Goals To gain the ability to design and implement a Smart System, to develop an Intelligent System, and to study how to combine and integrate Artificial Intelligence topics in depth and breadth.
Content Introduction to Intelligent Systems, Artificial Neural Networks, Evolutionary Computation, Fuzzy Logic, Expert Systems, Hybrid Intelligent Systems, Fuzzy Expert systems, Neural Expert Systems, Neuro-fuzzy Systems, Evolutionary Neural Networks.
Topics
WeeksTopics
1 Introduction to Intelligent Systems
2 Hybrid Intelligent Systems, Neural Expert Systems
3 Neural Fuzzy Systems and ANFIS
4 Expert Systems, Rule Based Expert Systems
5 Bayesian Reasoning, Certainty Factors
6 Evolutionary Computing
7 Evolutionary Computing
8 Machine Learning, Deep Learning, Fuzzy Logic
9 Machine Learning, Deep Learning, Fuzzy Logic
10 Fuzzy Expert Systems, Frame Based Expert Systems
11 Information Engineering and Data Mining Robotics Applications, Intelligent Systems in Business
12 Swarm Intelligence Algorithms, Suggestion Systems
13 Chat Robots, Natural Language Processing
14 Opinion Analysis, Collective Learning
Materials
Materials are not specified.
Resources
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam60Final Exam
Midterm Exam40Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes