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 (www.datajoyai.com). Introduction to data and AI basics Types of data (structured and unstructured) Data lifecycle and data quality Data cleaning and metadata Basics of R programming Data storage formats (CSV, JSON, Parquet) Databases, cloud storage, and APIs Introduction to machine learning Supervised and unsupervised learning How AI learns from data Real-world AI applications Basic statistics and data analysis Data visualization and charts Outlier detection Prompt engineering basics Evaluating AI outputs Human and AI collaboration AI ethics and fairness Privacy and responsible AI AI risks like bias and misinformation Hands-on labs and practical exercises
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Paperback. Zustand: new. Paperback. 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 AI and Data Literacy explores data basics, data quality, storage, machine learning, analytics, visualization, prompt engineering, AI evaluation, ethics, fairness, privacy, and responsible AI through practical labs and real-world examples. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9781969233371
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Paperback. Zustand: new. Paperback. 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 AI and Data Literacy explores data basics, data quality, storage, machine learning, analytics, visualization, prompt engineering, AI evaluation, ethics, fairness, privacy, and responsible AI through practical labs and real-world examples. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Bestandsnummer des Verkäufers 9781969233371
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Paperback. Zustand: new. Paperback. 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 AI and Data Literacy explores data basics, data quality, storage, machine learning, analytics, visualization, prompt engineering, AI evaluation, ethics, fairness, privacy, and responsible AI through practical labs and real-world examples. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9781969233371
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