Deep Learning

  • College Of Computing & Information Technology |


- Explain the basic mathematical foundation for machine learning techniques.
- Identify the main Deep Learning algorithms and their applicability in Machine Learning tasks.
- Explain details of layered-architectures and their learning algorithms.
- Explain how real-world problems are modelled and solved by Deep Learning techniques.
- Elaborate on the strengths of the state-of- the-art of Deep Learning techniques and the challenges that remain.
- Develop programs using a Deep Learning toolbox.
- Apply metrics for evaluating outcomes of Deep Learning program and analyzing results.


Computer Science bachelor`s degree Program


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Data will be available soon!

Course Content

content serial Description
1Why go deep?
3CNNs for classification
4CNNs for semantic segmentation
5Recurrent Neural Networks
7Boltzmann machines
8Restricted Boltzmann machines
10Basics of GANs
11Performance measures
12Performance analysis
13Deep models and reinforcement learning
14Explainable AI basics

Markets and Career

  • Generation, transmission, distribution and utilization of electrical power for public and private sectors to secure both continuous and emergency demands.
  • Electrical power feeding for civil and military marine and aviation utilities.
  • Electrical works in construction engineering.

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