Data science education provides tremendous opportunities but remains inaccessible to many communities. Increasing the accessibility of data science to these communities not only benefits the individuals entering data science, but also increases the field's innovation and potential impact as a whole. Education is the most scalable solution to meet these needs, but many data science educators lack formal training in education. Our group has led education efforts for a variety of audiences: from professional scientists to high school students to lay audiences. These experiences have helped form our teaching philosophy which we have summarized into three main ideals: 1) motivation, 2) inclusivity, and 3) realism. To put these ideals better into practice, we also aim to iteratively update our teaching approaches and curriculum as we find ways to better reach these ideals. In this manuscript we discuss these ideals as well practical ideas for how to implement these philosophies in the classroom.

翻译：数据科学教育提供了巨大机遇，但对许多社群而言仍难以触及。提升这些社群接触数据科学的可及性，不仅有利于进入数据科学领域的个体，更能增强该领域整体的创新力与潜在影响力。教育是满足这些需求最具可扩展性的解决方案，但许多数据科学教育者缺乏正规的教育培训。本团队已面向多元受众开展教育工作：从专业科学家、高中生到普通公众。这些经验塑造了我们的教学理念，并将其归纳为三大核心准则：1）动机激发，2）包容性，3）真实性。为更好地践行这些准则，我们致力于在探索更佳实现路径的过程中，迭代更新教学方法与课程体系。本文不仅讨论了上述准则，还提出了在课堂中落实这些理念的实践方案。