Learn core deep learning concepts including neuron composition, network architecture, activation functions, loss functions, optimizers, and forward and backward propagation. The course covers end-to-end model development using TensorFlow and Keras, including feature scaling, model compilation, evaluation, and prediction. It also discusses the limitations of ANN for NLP tasks and demonstrates practical business use cases of deep learning.