The astronomical growth of data has necessitated the need for educating well-qualified data scientists to derive deep insights from large and complex data sets generated by organizations. In this paper, we present our interdisciplinary approach and experiences in teaching a Data Science course, the first of its kind offered at the Wright State University. Two faculty members from the Management Information Systems (MIS) and Computer Science (CS) departments designed and co-taught the course with perspectives from their previous research and teaching experiences. Students in the class had mix backgrounds with mainly MIS and CS majors. Students' learning outcomes and post course survey responses suggested that the course delivered a broad overview of data science as desired, and that students worked synergistically with those of different majors in collaborative lab assignments and in a semester long project. The interdisciplinary pedagogy helped build collaboration and create satisfaction among learners.
The NC State All-campus Data Science and AI Project-based Teaching and Learning (ADAPT) Model: A mechanism for interdisciplinary engagement in workforce-relevant learning
North Carolina State University（北卡罗来纳州立大学）；College of William and Mary（威廉玛丽学院）
Unfolding the Interdisciplinary Complexities of Climate Science: Fuxi-Climate Foundational Model
College of Computer Science and Artificial Intelligence, Fudan University（复旦大学计算机科学技术学院）；Shanghai Innovation Institute（上海创新研究院）；Shanghai Academy of AI for Science（上海人工智能科学 academy）；Department of Environmental Science and Engineering, Fudan University（复旦大学环境科学与工程系）；School of Data Science, Fudan University（复旦大学数据科学与工程学院）；Fudan Development Institute, Fudan University（复旦大学发展研究院）；Shanghai Institute for Energy and Carbon Neutrality Strategy（上海能源与碳中和战略研究院）；Institute for Big Data, Fudan University（复旦大学大数据研究院）；MOE Laboratory for National Development and Intelligent Governance（国家发展与智能治理教育部重点实验室）
The theoretical and methodical foundations of usage of information and communication technologies in teaching higher mathematics engineering students in universities of the United States
Integrated Science, Technology, Engineering and Mathematics (STEM) Education through Active Experience of Designing Technical Toys in Vietnamese Schools
FAIR for AI: An interdisciplinary and international community building perspective
Argonne National Laboratory（阿贡国家实验室）；University of Chicago（芝加哥大学）；Duke University（杜克大学）；Lawrence Berkeley National Laboratory（劳伦斯伯克利国家实验室）；University of California Berkeley（加州大学伯克利分校）；University of California San Diego（加州大学圣地亚哥分校）；Lund University（隆德大学）；The University of Manchester（曼彻斯特大学）
