Pre-requisites: QSTBA 600, QSTBA 602, QSTBA 780, QSTBA 810, QSTBA 820. This course provides a basic introduction to the theory and implementation of artificial neural networks (ANNs) in Python. We will introduce students to Keras and PyTorch, Python packages / frameworks that support the implementation of neural networks. We will then develop an understanding of fundamental concepts behind neural network architecture. We will explore a variety of use cases, deal with various types of unstructured data (text, images, audio, time series), and gain hands-on experience, starting with the implementation of simple networks and building up towards harnessing the powers of more complex pre-trained ones. This is an intensive course. Students will pursue a hands-on group project over the duration of the course.

Note that this information may change at any time. Please visit the MyBU Student Portal for the most up-to-date course information.