Artificial intelligence is a large field that includes many techniques to make machines think, which means endowing this machine with intelligence, unlike, as we all know, the habitual intelligence exhibited by humans and animals. Therefore, in this course, we investigate the mimicking of human intelligence on machines by introducing a modern algorithm of artificial intelligence named the convolutional neural network, which is a technique of deep learning for computers to make the machine learn and become an expert. In this course, we present an overview of deep learning in which, we introduce the notion and classification of convolutional neural networks. We also give the definition and the advantages of CNNs. In this course, we provide the tricks to elaborate your own architecture of CNN and the hardware and software to design a CNN model. In the end, we present the limitations and future challenges of CNN.

The essential points tackled in this course are given as follows:

- What is deep learning?

- Why are computational intelligence algorithms used?

- Biomimetics inspiration of CNN from the brain

- Classification of deep learning (CNN)

- The kinds of deep learning algorithms

- Definition of convolutional neural networks

- Advantages of Convolutional Neural Network

- The aim of CNN

- Architecture of CNN

- Training and optimization of CNN parameters

- Hardware material used for CNN

- Software used for deep learning

- Famous CNN architecture

- Application of CNN

- Limitation of CNN

- Future and challenges of convolutional neural networks

- Conclusions