Education should not be a privilege but a common good. It should be openly accessible to everyone, with as few barriers as possible; even more so for key technologies such as Machine Learning (ML) and Data Science (DS). Open Educational Resources (OER) are a crucial factor for greater educational equity. In this paper, we describe the specific requirements for OER in ML and DS and argue that it is especially important for these fields to make source files publicly available, leading to Open Source Educational Resources (OSER). We present our view on the collaborative development of OSER, the challenges this poses, and first steps towards their solutions. We outline how OSER can be used for blended learning scenarios and share our experiences in university education. Finally, we discuss additional challenges such as credit assignment or granting certificates.

翻译：教育不应该是一种特权,而应该是一种共同利益。教育应该向所有人开放,尽可能少设置障碍;对于机器学习和数据科学等关键技术来说,更是如此。开放教育资源(OER)是提高教育公平性的关键因素。在本文中,我们描述了ML和DS对OER的具体要求,并说这些领域特别需要公布源文件,从而导致开放源教育资源(OSER)。我们提出了我们关于OSER合作发展的观点,这构成的挑战,以及解决这些挑战的第一步。我们概述了如何将OSER用于混合学习情景,并分享我们在大学教育方面的经验。最后,我们讨论了诸如信贷分配或发放证书等额外挑战。