I have been asked to teach a module named ''Supervised Learning'', and the module is not well set up with precise topics or references. In a three month teaching period starting from 7th January 2022-7th March, there will be 3 hours of lectures in a week. Thus, could anyone help me set up the topics and possible references for the students from the syllabus outline below?
''This module will introduce the framework of supervised learning. Students will learn the framework of linear models and see examples of their extensions to generalized linear models. General modelling principles will be discussed, and students will learn the models of failure encountered when working with flexible, nonparametric models. Several modern nonparametric methods for regression and classification will be considered, and their performance evaluated on datasets from a variety of scientific problem domains. The emphasis throughout will be on principled, uncertainty-aware modelling.''
PS: I am a researcher in applied mathematics only but appointed as a lecturer in a college, I have never read Machine learning before. Thus it will be a learning process for me too along with the students.