Data Science for the Internet of Things (IoT) University of Oxford

Overview

• The programme is based on a perspective of both AI and machine learning. AI is driven by deep learning algorithms. Deep learning is a wider case of machine learning based on automatic feature detection. IoT primarily involves data in time series formats (using AI algorithms like recurrent neural networks and long short-term memory (LSTMs)) and image-based data (using convolutional neural networks).
• Previous students have used the course to start a new career, for career progression or to have their skills upgraded by their employer.
• The course takes a problem solving approach and uses specific case studies from industry. Participants are expected to have a mind-set of exploration and to study and learn beyond the class material itself (depending on their existing familiarity with the subject matter).
• We cover handling large-scale IoT datasets and we aim to equip you with skills such as TensorFlow, Keras and AI in general, which can be used outside of IoT applications. Python is the primary language of the course and while we do not expect you to have full proficiency in it, we expect you to have a programming background.
• This is not an academic course, we focus on skills based/commercial products, however participants are expected to have an understanding of maths.