Developing Interactive Learning Resources for Python and Machine Learning

Abstract

This paper describes the process of developing learning resources for students in computing and offers various examples of the learning resources that were successfully developed as a result. Two main learning resources were developed from the project described in this paper: A supplementary technical guide and interactive workshops. The technical guide was found to be beneficial for different types of students such as students who are interested in the field of computing but, have not yet started their formal education on the field, students in computing who wish to review concepts they were previously taught, and students who wish to mentor other students in programming concepts. On the other hand, the interactive workshops written as Jupyter notebooks were found to be beneficial for community outreach activities since they contain both examples and exercises that presenters may easily discuss while the audience is interacting with code relating to each example and exercise. Key terms – Jupyter Lab, Machine Learning, Pythontechnical guide, and Workshops