Computer vision and relevant algorithms have started to make their way in various applications and become more relevant in our daily life: face detection, drones, and self-driving cars to name a few. Recent developments in deep neural network architectures, large datasets and training techniques have greatly advanced the performance of these state-of-the-art visual recognition systems. This course will investigate common deep learning architectures with a focus on learning effective models for various computer vision tasks. Part of the course evaluation involves student-proposed course projects focusing on building a working computer vision system using deep learning algorithms and techniques.