Massive Open Online Courses (MOOCs) have transformed the educational landscape, offering scalable and flexible learning opportunities, particularly in data-centric fields like data science and artificial intelligence. Incorporating AI and data science into MOOCs is a potential means of enhancing the learning experience through adaptive learning approaches. In this context, we introduce PyGlide, a proof-of-concept open-source MOOC delivery system that underscores autonomy, transparency, and collaboration in maintaining course content. We provide a user-friendly, step-by-step guide for PyGlide, emphasizing its distinct advantage of not requiring any local software installation for students. Highlighting its potential to enhance accessibility, inclusivity, and the manageability of course materials, we showcase PyGlide's practical application in a continuous integration pipeline on GitHub. We believe that PyGlide charts a promising course for the future of open-source MOOCs, effectively addressing crucial challenges in online education.

翻译：大规模开放在线课程（MOOC）已彻底改变了教育格局，提供了可扩展且灵活的学习机会，尤其在数据科学和人工智能等数据密集型领域。将人工智能与数据科学融入MOOC是提升学习体验的潜在途径，可通过自适应学习方法实现。在此背景下，我们提出了PyGlide——一个概念验证型开源MOOC交付系统，它强调课程内容维护中的自主性、透明性与协作性。我们提供了用户友好的PyGlide分步指南，并着重强调其无需学生在本地安装任何软件的独特优势。通过展示PyGlide在GitHub持续集成流水线中的实际应用，我们突显了其在提升可及性、包容性及课程材料易管理性方面的潜力。我们相信，PyGlide为开源MOOC的未来描绘了光明前景，有效应对了在线教育中的关键挑战。