Neural Networks

This course covers artificial neural networks and their practical applications. Coursework emphasizes fundamental models and algorithms starting with McCulloch-Pitts and Perceptron models, Multi-Layer Perceptron (MLP) networks, backpropagation algorithm, activation functions, convolutional neural networks, and recurrent neural networks. Students will gain hands-on experience by using Keras and TensorFlow to build and train models for solving various classification/prediction problems.  

Note: Check with the institution regarding start/end dates, prices, and delivery method. These may vary according to program, section, and/or semester.