Information Package / Course Catalogue
Introduction to Artificial Neural Networks
Course Code: BİS524
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 1
Prt.: 0
Credit: 1
Lab: 0
ECTS: 2
Objectives of the Course

This course provides basic information about neural networks and provides application examples. Medical usage is included.

Course Content

Base concepts of artificial neural networks, theory of artificial neural networks, activation functions, learning algorithms.

Name of Lecturer(s)
Learning Outcomes
1.To be able to comprehend basic ANN
2.To be able to understand Artificial Neural Network structure
3.To be able to comprehend ANN learning algorithms
4.To be able to comprehend the matters to be considered in the design of ANN
5.To be able to explore ANN application areas
Recommended or Required Reading
Weekly Detailed Course Contents
Week 1 - Theoretical
Basic definitions and concepts
Week 2 - Theoretical
ANN's development history
Week 3 - Theoretical
Structure and basic elements of ANNs
Week 4 - Theoretical
ANN models
Week 5 - Theoretical
Learning and adaptation, neural networks' learning rules-1
Week 6 - Theoretical
Learning and adaptation, neural networks' learning rules-2
Week 7 - Theoretical
Single-layer feedback networks
Week 8 - Intermediate Exam
Midterm exam
Week 9 - Theoretical
Single-layer feedback networks
Week 10 - Theoretical
Multi-layer feedforward networks-1
Week 11 - Theoretical
Multi-layer feedforward networks-2
Week 12 - Theoretical
Activation functions
Week 13 - Theoretical
Applications of neural network-1
Week 14 - Theoretical
Applications of neural network-2
Week 15 - Theoretical
Literature review and discussion
Week 16 - Final Exam
Final exam
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
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