Information Package / Course Catalogue
| Course Code | : CSE422 |
| Course Type | : Area Elective |
| Couse Group | : First Cycle (Bachelor's Degree) |
| Education Language | : English |
| Work Placement | : N/A |
| Theory | : 2 |
| Prt. | : 2 |
| Credit | : 3 |
| Lab | : 0 |
| ECTS | : 6 |
To understand and implement articial neural networks in real life
This course presents an overview of neural networks and machine learning techniques and their implementation in real life.
| Lec. Mahmut SİNECEN |
| 1. | O1. Explore the fundamental principles of machine learning techniques |
| 2. | O2. Assess the basic concepts of supervised and unsupervised algorithms |
| 3. | O3. Convert and normalize collected information into datasets appropriate for analysis |
| 4. | O4. Implement machine learning techniques over prepared samples |
| 5. | O5. Analyse the results obtained from the executed experiments |
| 6. | O6. Demonstrate and evaluate the algorithms and the results |
| 1. | Introduction to Machine Learning, E. Alpaydin, MIT Press, 2009 |
| 2. | Neural Networks and Learning Machines, 3rd Edition, S. O. Haykin, Pearson, 2009 |
| Type of Assessment | Count | Percent |
|---|---|---|
| Midterm Examination | 1 | %40 |
| Final Examination | 1 | %40 |
| Quiz | 2 | %10 |
| Assignment | 2 | %10 |
| Activities | Count | Preparation | Time | Total Work Load (hours) |
|---|---|---|---|---|
| Lecture - Theory | 14 | 0 | 2 | 28 |
| Lecture - Practice | 14 | 0 | 2 | 28 |
| Assignment | 2 | 0 | 5 | 10 |
| Individual Work | 14 | 0 | 3 | 42 |
| Quiz | 2 | 0 | 5 | 10 |
| Midterm Examination | 1 | 0 | 10 | 10 |
| Final Examination | 1 | 0 | 22 | 22 |
| TOTAL WORKLOAD (hours) | 150 | |||
PÇ-1 | PÇ-2 | PÇ-3 | PÇ-4 | PÇ-5 | PÇ-6 | PÇ-7 | PÇ-8 | PÇ-9 | PÇ-10 | PÇ-11 | |
OÇ-1 | 5 | 4 | 4 | 4 | 3 | ||||||
OÇ-2 | 4 | 5 | 5 | 5 | 5 | ||||||
OÇ-3 | 3 | 3 | 3 | 3 | 2 | ||||||
OÇ-4 | 3 | 4 | 4 | 3 | 3 | ||||||
OÇ-5 | 2 | 3 | 3 | 4 | 3 | ||||||
OÇ-6 | 3 | 2 | 2 | 3 | 4 | ||||||