Abstract

STEM Fellowship’s Undergraduate Big Data Challenge (UnBDC) is an inquiry-driven and experiential learning program that invites students from across the country to strengthen their problem-solving and critical thinking skills while gaining familiarity with the fundamentals of data science. By allowing students to undertake independent research projects that tackle real-world public health and bioinformatics problems, the BDC fosters scientific inquiry and prompts new and innovative ideas. This year, we invited students to investigate the theme of Infodemiology for the Future of Digital and Public Health. It allowed students to explore practical applications and insights of infodemiology to discover breakthrough connections in Digital and Public Health using open social, demographic, and health data. Students explored many topics, ranging from using Twitter machine learning for fighting the COVID-19 infodemic, to the sentiment comparison between real and fake COVID-19 news articles. We developed in-depth learning modules designed to lead the student from zero-knowledge to an elementary working proficiency in data science. The students learn a broad range of data analytics tools, methods and programming languages which are useful for uncovering hidden patterns, trends in structured and unstructured data. Some of the skills the students learnt and used includes Data Visualization, Classification, Statistics and Data Handling, Overleaf etc. On behalf of STEM Fellowship, we extend our sincere congratulations to all students who participated in the challenge, and wish them the best for their future endeavours. It has been a privilege for us to witness the analytical capabilities of the next generation of students firsthand, and we are certain all entrants will continue to demonstrate excellence in their respective careers.

Full Text
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