In recent years, the construction of platforms for mathematics, data science (DS), and artificial intelligence (AI) education at universities in Japan has been progressing gradually. On the other hand, the reality is that the next generation of children are already learning AI and DS education, as seen in the GIGA School Project and other initiatives that have made IT education compulsory in primary and secondary education. There is an urgent need to spread AI and DS education at universities to bridge this generational gap, but this does not necessarily mean that education is only available to students who have mastered programming.

In this paper, we present a practical example of a hands-on class on AI using a non-programming machine learning service for students in the humanities and social sciences. Students in the humanities and social sciences are not necessarily good at mathematics or information-related subjects, or they have not studied them yet. In addition, the level of acquisition of ICT knowledge and skills is not sufficient, and programming experience is not a prerequisite in most cases.

In the practice, a classification method using a free machine learning service was presented to the students, and they practiced classification of images and sounds to the extent that they were able to do so. This service can be operated almost entirely with the mouse, and students can easily check the results using AI without having to create a program. We will discuss the results and effects of this practice in a setting that allows students to recognize their own skill level and produce satisfactory results to the extent possible.

Keywords: Non-Programming Education, Artificial Intelligence, Image Processing, Classification, Google Teachable Machine.