In this study, data science is defined as something that involves three fields: science such as mathematical statistics, technology such as information and communication, and management of various tasks and projects. Data science is being used in many areas in today's society. However, there is a shortage of people who can take on this challenge, namely data scientists, and there is an urgent need to educate and train them. One educational method is to generate data using real teaching materials and learn by respecting experience and autonomy. Examples of real teaching materials include coin shooting, paper helicopters, and paper gliders, and several reports have been published so far. In those reports, the so-called PDCA cycle of plan, do, consider, and act was adopted to solve problems and achieve tasks in tasks and projects, and this framework was maintained in data science education. It is also pointed out that in the future, it will be important to develop the ability to observe not only formatted and managed data, but also small data and tail data before processing, set new hypotheses based on individuality and experience, and connect them to innovation. In this presentation, we will systematically organize these and discuss the possibility of data science education and innovation from it.
