Result: Organization of a Hybrid Multi-Platform Online Course on 'Machine Learning' for Higher Education System
Further Information
The article deals with the experience of developing and integrating the author’s multiplatform online course “Machine Learning” into the educational process of higher education institutions. On the basis of international experience the recommendations on the integration of the online course content into the educational environment of the university are developed. The requirements to the choice of an educational platform when teaching programming are discussed. The key points concerning the selection of training content, its quality assessment, as well as its implementation in the educational process are highlighted on the example of the discipline “Machine Learning”, developed at the Department of Mathematics at A.I. Herzen Russian State Pedagogical University for bachelors studying in the direction 01.03.02 “Applied Mathematics and Informatics”. The author’s composition of Python 3 programming language libraries for generating practical tasks for solving problems of different complexity and organising mini-research in the field of machine learning is presented. Jupiter Notebook, Stepik, Moodle Herzen platforms are specified as the means of training organisation. When selecting and creating task material, domestic resources of olympiad programming: Kaggle and Codeforces were actively used. The first results of the experimental testing of the methodology at the Faculty of Mathematics of the Herzen Russian State Pedagogical University are discussed.