Theoretical and practical aspects of the implementation of Machine Learning software projects. Students will be able to comply to data-based software design methods, choosing the most adequate tool for the problem at hand.
Machine Learning Operations
Learning Goals
Program in pills
Introduction to Software Engineering, Software Processes (activities, cope with chances and RUP), Agile Software Development, UML, Software Versionig and Testing, Scrum and Data-Driven Modelling.
ML Operations: introduction, People, Rules, Feature, Concepts, Developing Models, Production, Monitoring, Governance, Testing, Data Representation, Process Mining Analysis
Area
Computer Science and Intensive Computing
Curriculum Foundations
TAF Type
Curriculum Industry
TAF Type
Curriculum Health
TAF Type
Curriculum Economy
TAF Type
SSD
ECTS
Semester
Lecturers
Sylvio Barbon Junior
Stefano Cozzini