| 1 | Makine Öğrenmesine Giriş | 1 |
| 2 | Makine Öğrenmesi Temelleri | 1 |
| 3 | Derin Öğrenme Araçları - Caffe, Torch, TensorFlow, Theano | 1 |
| 4 | Feedforward Deep Networks | 1 |
| 5 | Regularization of Deep or Distributed Models | 1 |
| 6 | Optimization for Training Deep Models | 1 |
| 7 | Convolutional Networks | 1 |
| 8 | Sequence Modeling: Recurrent and Recursive Nets | 1 |
| 9 | Structured Probabilistic Models for Deep Learning | 1 |
| 10 | Linear Factor Models and Auto-Encoders | 1 |
| 11 | Computer Vision Uygulamaları | 1 |
| 12 | Big Data Uygulamaları | 1 |
| 13 | Natural Language Processing Uygulamaları | 1 |
| 14 | Speech Processing Uygulamaları | 1 |