AI and Data Literacy: Student Edition

AI and Data Literacy is designed for independent learners or college-level courses in data analytics, statistics, and artificial intelligence. The text integrates conceptual foundations with hands-on learning through applied labs, real-world datasets, and guided exercises. Intended for full-semester academic use, this edition supports students and instructors in developing practical AI and data literacy skills.Learning resources are available from the publisher ().Introduction to data and AI basicsTypes of data (structured and unstructured)Data lifecycle and data qualityData cleaning and metadataBasics of R programmingData storage formats (CSV, JSON, Parquet)Databases, cloud storage, and APIsIntroduction to machine learningSupervised and unsupervised learningHow AI learns from dataReal-world AI applicationsBasic statistics and data analysisData visualization and chartsOutlier detectionPrompt engineering basicsEvaluating AI outputsHuman and AI collaborationAI ethics and fairnessPrivacy and responsible AIAI risks like bias and misinformationHands-on labs and practical exercises