In the contemporary workplace, data scientists who are capable of interdisciplinary collaboration are in high demand. Universities need to provide data science students with a plethora of learning opportunities that involve collaboration in interdisciplinary contexts and engagement with industry partners. Curtin University and Lab Tests Online Australasia (LTO^AU) collaborated to provide an interdisciplinary, industry-focused learning experience for data science students. Upon completing the project, students reported improved understanding of the range of applications for data science skills. The experience delivered opportunities for greater self-awareness and highlighted the importance of teamwork, decision-making and leadership skills. This chapter presents Interdisciplinary Project-based Work-Integrated Learning (IPjWIL), an educational approach that equips data science students with the necessary skills to navigate the future world of work. The results of the pilot project described demonstrate how interdisciplinary, industry-focused learning experiences enhance the capabilities of data science students, thereby augmenting employability.

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培养数据科学学生的就业能力：一种跨学科、以行业为中心的方法

在当代工作场所，能够进行跨学科协作的数据科学家的需求量很大。大学需要为数据科学专业的学生提供大量的学习机会，包括跨学科合作和与行业合作伙伴的接触。科廷大学和实验室在线测试澳大利亚 (LTO ^AU)) 合作为数据科学专业的学生提供跨学科、以行业为中心的学习体验。完成该项目后，学生们报告说，他们对数据科学技能的应用范围有了更好的理解。这段经历为提高自我意识提供了机会，并强调了团队合作、决策和领导技能的重要性。本章介绍了基于跨学科项目的工作集成学习 (IPjWIL)，这是一种教育方法，可让数据科学专业的学生掌握必要的技能，以驾驭未来的工作世界。所描述的试点项目的结果展示了跨学科、以行业为中心的学习体验如何增强数据科学学生的能力，从而增强就业能力。