MOOC - Artificial Intelligence Technician
Deep Learning and Neural Networks
The last unit of this job role is an introduction to deep learning, a particular branch of artificial intelligence, and neural networks. It provides learners an elaborated description of Deep Learning, differentiating it from Machine Learning and Artificial Intelligence.
Neural Networks Topology:
This learning element gives a detailed description of neural networks’ architecture focusing on its constituents, the organization of those constituents, the architectures of the conventional neural networks and their applicability.
AIT.U3.E4.PC1
The student understands the key parameters in a neural network\'s architecture.
AIT.U3.E4.PC2
The student knows some of the most common neural networks like perceptron, multi-layer perceptron, feed-forward, backpropagation, etc.
AIT.U3.E4.PC3
The student understands the main differences between those types of architectures.
AIT.U3.E4.PC4
The student knows the different use cases of each architecture.
AIT.U3.E4.PC5
The student is able to critically select the architecture that best fits a specific problem or situation.