36113 Applied Data Science for Innovation
4cp; 6 days, distanceAnti-requisite(s): 36106 Machine Learning Algorithms and Applications
Notes
This subject is only available via UTS open as microcredential subjects and is not suitable for enrolled MDSI students.
Description
This subject provides participants a holistic view of driving innovation using Machine Learning. Participants will not only acquire relevant technical skills for building supervised and unsupervised models such as linear regression, RandomForest or k-Means but also other important skills that help them to manage and deploy ML solutions as a whole. While learning core ML knowledge and skills, participants are introduced to Agile methodology and running controlled ML experiments to deal with uncertainty. They are also exposed to data citizenship and responsibilities of providing accurate, ethical predictions and see how to manage efficiently the lifecycle of ML solutions in production.
Detailed subject description.