Description of Individual Course Units
Course Unit CodeCourse Unit TitleType of Course UnitYear of StudySemesterNumber of ECTS Credits
İM502APPLICATIONS OF ARTIFICIAL NEURAL NETWORK IN CIVIL ENGINEERINGElective116
Level of Course Unit
Second Cycle
Objectives of the Course
Name of Lecturer(s)
Doç.Dr.Murat Ay
Learning Outcomes
1
2
3
4
5
Mode of Delivery
Formal Education
Prerequisites and co-requisities
Recommended Optional Programme Components
Course Contents
Weekly Detailed Course Contents
WeekTheoreticalPracticeLaboratory
1Introduction
2
3
4
5
6
7
8
9
10
11
12
13
14
15Final exam
Recommended or Required Reading
1. Yapay Zekâ Uygulamaları, Prof. Dr. Çetin Elmas 2. Neural Networks with R: Smart models using CNN, RNN, deep learning, and artificial intelligence principles, 2017, Giuseppe Ciaburro, Balaji Venkateswaran 3. Artificial Neural Networks: An Introduction, 2005, Kevin L. Priddy and Paul E. Keller
Planned Learning Activities and Teaching Methods
Assessment Methods and Criteria
Term (or Year) Learning ActivitiesQuantityWeight
Quiz220
Attending Lectures1420
Criticising Paper520
Individual Study for Quiz220
Homework120
SUM100
End Of Term (or Year) Learning ActivitiesQuantityWeight
Final Examination125
Report Preparation125
Report Presentation125
Individual Study for Final Examination125
SUM100
Term (or Year) Learning Activities50
End Of Term (or Year) Learning Activities50
SUM100
Language of Instruction
Turkish
Work Placement(s)
None
Workload Calculation
ActivitiesNumberTime (hours)Total Work Load (hours)
Final Examination111
Quiz212
Attending Lectures14342
Report Preparation12525
Report Presentation111
Criticising Paper5315
Individual Study for Final Examination12020
Individual Study for Quiz11515
Homework12020
TOTAL WORKLOAD (hours)141
Contribution of Learning Outcomes to Programme Outcomes
LO1
LO2
LO3
LO4
LO5
* Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High
 
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