Artificial Neural Networks and Deep Learning

Catalog description

Deep learning, as a field of computer science study, is a branch of machine learning that focuses on the development and application of deep artificial neural networks. The computing model of an artificial neural network (ANN) consists of layers of nodes called perceptrons or artificial neurons, which can learn complex patterns in data. The deep learning model extracts layered data representations of complex data to maximize task performance. Deep learning has a wide range of applications, such as object recognition, classification, prediction, natural language processing, speech recognition, fraud detection, recommender systems, and other scientific and healthcare applications. This course covers the theory and problem-solving techniques relevant to the foundations and applications of deep learning and modern deep neural networks, the methodology of deep learning model development, evaluation, validation, and optimization. The course requires a strong foundation in algorithms, programming, and mathematics.