This module introduces computer vision and deep learning, covering a variety of essential topics to provide students with the knowledge and practical skills needed to succeed in this exciting field. Students will learn about the history of computer vision and image formation, as well as practical skills like edge detection, image features, SIFT, image matching, and image segmentation. The course also introduces linear programming, tensors, and GPUs, before delving into the essential concepts of perceptrons and neural networks. The module also introduces PyTorch and covers the essential steps for preparing datasets, building, training, testing, and validating models. The highlight of the module is a practical image classification project using PyTorch, which lays a strong foundation in both theory and practical applications.

Values:

• Computer Vision and Deep Learning are changing the way everything works today, from airplanes to autonomous cars. This module introduces students to the fundamentals of these state-of-the-art technologies.

• This module prepares the students to start working on applications in various fields, such as healthcare, transportation, and entertainment.

• This module prepares students for basic internships in both small and large businesses.