Courses - DL Foundation

This is an introductory course designed to provide participants with a comprehensive understanding of deep learning principles and techniques. Through a combination of theoretical concepts and practical exercises, participants will learn the fundamentals of deep neural networks, including feedforward networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs). The course covers key topics such as activation functions, loss functions, optimization algorithms, and regularization techniques. Participants will also gain hands-on experience in building and training deep learning models using popular frameworks such as TensorFlow and PyTorch. By the end of the course, participants will have a solid foundation in deep learning and be ready to tackle more advanced topics in the field.