Curricula

Objective

Deep learning uses deep neural networks to solve complex problems. You understand the basics of deep learning, including the theory and applications of neural networks. You learn to use deep learning libraries and implement different architectures of neural networks.

EUR-ACE Knowledge and Understanding
You know the basics of deep learning, including the theory of neural networks.

EUR-ACE Engineering practice
You know how to use deep learning libraries. You know how to use different architectures of deep neural networks. You know how to apply deep learning in different application domains, such as image recognition and natural language processing.

Content

In this course, you will learn the fundamentals of deep learning and how to use deep neural networks to solve complex problems. You will gain an understanding of the theory and applications of neural networks. You will learn to use deep learning libraries and implement various neural network architectures. By the end of the course, you will be able to apply deep learning to different application areas, such as image recognition and natural language processing.

Basic theory of deep learning
Perceptron
Deep learning libraries: TensorFlow and Keras
The theory of neural networks
Architectures of neural networks
Advanced deep learning methods
Applications of deep neural networks (image recognition, NLP)

Qualifications

Basics of Programming

Assessment criteria, satisfactory (1)

Sufficient (1)
You only know the basics of deep learning. You know how to use some deep learning libraries. You know how to make a simple neural network architecture. You know how to use deep learning in a precisely defined problem.

Satisfactory (2)
You know the basics of deep learning. You know how to use some deep learning libraries. You recognize some architectures of deep neural networks. You know how to use deep learning in some application domains.

Assessment criteria, good (3)

Good (3)
You know the basics of deep learning. You know how to use some deep learning libraries. You know how to use some deep neural network architectures. You know how to use deep learning in different application domains.

Very good (4)
You know the basics of deep learning and the theory of neural networks. You know how to use and compare deep learning libraries. You know how to use deep neural network architectures and analyze the obtained results. You know how to apply deep learning in different application domains.

Assessment criteria, excellent (5)

Excellent (5)
You can explain the basics of deep learning and the theory of neural networks. You know how to choose the most appropriate deep learning libraries with justification. You know how to use deep neural network architectures suitable for the given business problems. You know how to apply deep learning and justify the obtained results in different application domains.