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The course introduces students to the artificial neural networks (ANNs) and their use in modern machine learning for tasks such as classification in many application domains. Students study the foundations of neural nets including neurons, activation and error functions, neural network types and architectures, backpropagation and gradient descent. Also covered is the history and origins of the connectionist school of AI.