Deeper Learning By Doing: Integrating Hands-On Research Projects Into a Machine Learning Course
arXiv:2107.13671
Abstract
Machine learning has seen a vast increase of interest in recent years, along with an abundance of learning resources. While conventional lectures provide students with important information and knowledge, we also believe that additional project-based learning components can motivate students to engage in topics more deeply. In addition to incorporating project-based learning in our courses, we aim to develop project-based learning components aligned with real-world tasks, including experimental design and execution, report writing, oral presentation, and peer-reviewing. This paper describes the organization of our project-based machine learning courses with a particular emphasis on the class project components and shares our resources with instructors who would like to include similar elements in their courses.
This paper was accepted to the Teaching Machine Learning Workshop at ECML 2021 (https://teaching-ml.github.io/2021/). Reviews and comments are available at https://openreview.net/forum?id=yFPqbprG2Qb¬eId=rSPC7tA6Pi_