Experiences from Teaching Practical Machine Learning Courses to Master's Students with Mixed Backgrounds

Omar Shouman, Simon Fuchs, Holger Wittges

Keywords: Teaching Machine Learning, Practical Courses, Teaching Deep Learning, Teaching Experience Report, Machine Learning Projects

TL;DR: The paper summarizes experiences from teaching practical machine learning master-level courses and gives recommendations on methods and techniques to use when conducting similar courses.

Abstract: Machine learning education has become more accessible and relevant to students from various backgrounds. Practical courses complement theoretical lectures by focusing on applied machine learning. In this work, we report about our experiences from teaching two machine learning practical courses to master students from different study programs; an introductory and an advanced course. We present a summary of the teaching and evaluation methods used in both courses. We summarize our experiences and the feedback collected from the students through a survey. We conclude with our recommendations on teaching and designing practical machine learning courses.