Deep Learning Fundamentals

A deep dive into the principles and techniques of deep learning. This course covers neural networks, backpropagation, and popular architectures such as CNNs and RNNs. Students will learn to implement deep learning models using frameworks like TensorFlow and Keras, understand their theoretical foundations, and apply them to complex problems such as image and sequence data analysis.