SCOPE OF DATA SCIENCE AND CUTTING-EDGE COMPUTATIONAL METHODS TO IMPROVE HUMAN WELFARE

CSE

Data science is an amalgamation of various techniques, including statistics, computer programming, hacking skills, and domain-specific expertise, among others. This interdisciplinary approach opens up promising opportunities for social work research and intervention. Practitioners can leverage data science methods to elevate the quality of their services across different practice levels. This article delves into the essential concepts of data science as a novel set of methodologies, tools, and technologies. Furthermore, it explores the relevance of machine learning techniques in identifying new skills and methodologies that can bolster social work interventions and evidence-based practice. Integrating data science into social work practice presents a unique challenge— a shift in the focus of interventions. Instead of solely seeking an understanding of the underlying causes of social issues, data science facilitates data-driven decision-making to predict and address these issues. While this shift may be perceived as limiting, it also holds the potential to offer exciting opportunities, depending on the context and needs of users and professionals in the field

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