The main purpose of this course is to provide the most fundamental knowledge to the students so that they can program on the framework of deep learning. Those students who become interested in deep learning may go on to graduate schools for further study.
This course helps students understand the capabilities, challenges, and consequences of deep learning and prepares students to participate in the development of leading-edge AI technology. In this course, students will build and train those architectures such as Convolutional Neural Networks, Transformers, and learn how to make them better with strategies such as Dropout, BatchNorm, and more. Get ready to master theoretical concepts and their industry applications using Python, NumPy and PyTorch and tackle real-world cases.
