Machine Learning Engineering

The theoretical and practical aspects of applied machine learning are themselves clearly challenging to master. However, even the mastery of these aspects does not prepare one to build interfaces between the model solution and the real world. Moreover, it does not inform development patterns that ensure maintainable and reliable solutions that work as expected and according to specification. The aim of this course is to introduce students to a general machine learning engineering framework, and to provide them with the necessary knowledge and skills to efficiently create maintainable machine learning systems of high quality.