Data Science Fundamentals provides comprehensive introduction to data science principles and methodologies essential for librarians and information professionals. The work introduces core data science concepts covering statistics, programming, visualization, and data analysis techniques. Coverage addresses data literacy, machine learning basics, and practical applications in information contexts. The book explores data ethics, privacy considerations, and responsible data practices. Topics include database management, data quality assessment, and interpretation methodologies. Designed for librarians, information professionals, and information science students, this resource develops foundational data science competencies supporting contemporary library and information services. Implementation strategies and practical examples strengthen learning outcomes. The book offers step-by-step guidance on implementing data science tools within library systems, addressing how information professionals can integrate these technologies to enhance service delivery, improve decision-making, and support patron research needs. Case studies from academic, public, and special libraries demonstrate real-world applications. Readers gain practical experience in data visualization, data interpretation, and strategic analysis relevant to contemporary library environments.