By Immanuel Williams, Adam Del Rio, Emily Zhu, Ken Xie
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The integration of Application Programming Interface (API) usage in data science and statistics education is a critical stride towards aligning classroom instruction with industry practices. This presentation emphasizes the importance of embedding API-centric lessons within data science, statistics, and computer science courses that cater to lower-level college computer science students and those in upper-division data science and statistics courses with 30 to 45 students. We propose a structured teaching approach that leverages JSON data structures and data frames, emphasizing Spotify's API to illustrate the process of building libraries in R or Python. The methodology we present aims to demystify API calls, function implementation, and library application, with a strong emphasis on interpreting API documentation—a crucial skill for data scientists tasked with drawing actionable insights from data. We employ cloud-based technology solutions that enable interactive participation and effective screen sharing in our dynamic classroom environment. Our discussion narrows down to web APIs, specifically RESTful APIs, given their widespread application in software engineering and web development. This focus prepares students to proficiently handle data requests across various domains. By adopting this approach, educators can provide students with practical, relevant tools for data analysis and manipulation, ensuring they can contribute effectively to data-driven decision-making in their future careers. This presentation will navigate through the intricacies of API integration in academic settings, demonstrating its significance for a comprehensive data science education.