Dive into advanced deep learning concepts and practical implementation with Keras in this comprehensive tutorial and assignment session. Explore neural network architectures like VGG and DenseNet, delve into residual connections, and uncover the intricacies of autoencoders and GANs. Learn essential techniques for importing packages, managing batch sizes, and ensuring reproducibility in your deep learning projects. Gain hands-on experience through guided examples and a practical assignment, enhancing your skills in building and optimizing neural networks using the Keras framework.