| Course Objectives: |
Understanding the basics of deep learning, using open source libraries related to deep learning, developing deep learning applications.
|
| Course Content: |
Mathematical background, tensor operations, Graident descent, backpropagation, Keras deeplearning library , Machine learning models, Convolutional neural networks (convnets), transfer learning ,metin verileriyle derin öğrenme, recurrent neural networks, 1D convnets , Keras functional API, Generative deep learning, current topics
|
| Week |
Subject |
Related Preparation |
| 1) |
Introduction, Artificial Intelligence, Machine Learning and Deep Learning |
none |
| 2) |
Mathematical background, tensor operations, activation functions |
none |
| 3) |
Gradient descent and variants, loss functions |
none |
| 4) |
Feedforward networks and training, Keras deep learning library |
none |
| 5) |
Data preprocessing, regularization methods |
none |
| 6) |
Convolutional neural networks (convnets) |
none |
| 7) |
Transfer learning |
none |
| 8) |
Text processing, embedding layers |
none |
| 9) |
Sequence processing, Recurrent neural networks (RNN) |
none |
| 10) |
Simple RNN,LSTM, GRU |
none |
| 11) |
Keras functional API |
none |
| 12) |
Generative deep learning |
none |
| 13) |
Contemporary deep learning topics |
none |
| 14) |
Presentations |
none |
| |
Program Outcomes |
Level of Contribution |
| 1) |
Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in complex engineering problems. |
2 |
| 2) |
Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. |
2 |
| 3) |
Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose |
2 |
| 4) |
Ability to devise, select, and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively. |
3 |
| 5) |
Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions. |
2 |
| 6) |
Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. |
1 |
| 7) |
Ability to communicate effectively in Turkish, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. |
1 |
| 8) |
Knowledge of the global and societal impacts of engineering practices on priority issues such as health, environment and safety and contemporary issues; knowledge of the legal aspects of engineering solutions. awareness of the consequences |
1 |
| 9) |
Consciousness to behave according to ethical principles and professional and ethical responsibility; knowledge on standards used in engineering practice. |
1 |
| 10) |
Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and knowledge about sustainable development. |
2 |
| 11) |
Ability to design systems to meet desired needs |
2 |
| 12) |
Ability to apply basic sciences in the field of computer engineering |
2 |
| 13) |
Ability to implement designs by experiments |
3 |
| 14) |
Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself. |
2 |
Istanbul Health and Technology University INFORMATION PACKAGE / COURSE CATALOGUE