• ANN architecture: neurons, layers, and activation functions

  • Perceptron and multilayer perceptron (MLP) models

  • Backpropagation and gradient descent optimization

  • Developing and training ANN models using TensorFlow/Keras

  • Hands-on: Implementing ANNs for classification tasks