University of Technology Sydney

36113 Applied Data Science for Innovation

4cp; 6 days, distance
Anti-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.

Access conditions

Note: The requisite information presented in this subject description covers only academic requisites. Full details of all enforced rules, covering both academic and admission requisites, are available at access conditions and My Student Admin.