Computational Photography and low-level vision are pivotal research areas within Computer Vision, significantly impacting both academia and industry. Despite their importance, progress in these fields often lags behind areas like generative AI, primarily due to the scarcity of standardized datasets, clear benchmarks, and limited transparency from camera manufacturers. This tutorial bridges the gap between academic research and industry applications by providing an in-depth, hands-on exploration of computational photography and imaging using deep learning. Collaboratively presented by leading academic researchers and prominent industry experts from Sony, this tutorial systematically covers learned Image Signal Processors (ISPs), cutting-edge transformer and convolutional neural network architectures for image restoration and enhancement, and the development of realistic synthetic data generation pipelines. Attendees will acquire practical skills in dataset creation, realistic pipeline simulation, and evaluation protocols, empowering them with the tools and insights needed to accelerate innovation in this field.