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{ "item_title" : "SQL Mastery Series for AI, Data Science & Modern Computing", "item_author" : [" Uthayasooriya Amarasena "], "item_description" : "The journey of this volume began with a simple but profound vision: to empower learners to move beyond memorizing commands and instead think with SQL - to see queries not as isolated instructions, but as tools for intelligent analysis, structured reasoning, and real-world problem solving.In the early chapters, the learner was introduced to basic retrieval and filtering, the essential grammar of databases. Gradually, these skills expanded into aggregation, joins, and optimization, mirroring the natural progression from curiosity to mastery. Each section was carefully designed to build confidence, ensuring that learners could not only write queries but also interpret, refine, and apply them in diverse contexts.The applied labs - spanning healthcare, retail, education, and AI workflows - were chosen deliberately. They demonstrate how SQL is not confined to classrooms or textbooks, but is a living language of data that powers patient dashboards, revenue reports, student progress trackers, and machine learning pipelines. By embedding these scenarios, the book bridges theory with practice, preparing learners for professional challenges.Queries are not presented as rote formulas, but as logical expressions of thought. Learners are encouraged to ask: Why does this query work? How does it scale? What insight does it reveal? In answering these questions, they cultivate a mindset that transcends syntax and embraces analysis. Finally, the self-assessment sections and mini projects ensure that learning is active, reflective, and integrative. By testing theory, solving practical challenges, and designing small systems, learners consolidate their skills and prepare for the transition into Volume 3, where database design, advanced optimization, and AI-driven analytics await.This book is written with gratitude - to the mentors who shaped its philosophy, the colleagues who refined its clarity, the learners whose curiosity inspired its pedagogy, and the communities whose real-world challenges gave it relevance. May it serve as both a guide and companion on the learner's journey from basic queries to intelligent analysis, and onward to the design of robust, ethical, and future-ready data systems.Teaching Philosophy of This VolumeThis volume transforms the learner from a beginner who knows basic SQL syntax into a confident data explorer capable of retrieving, filtering, manipulating, and summarizing information from real-world databases.Learning StyleStorytelling-based explanationsMnemonics for rapid memory retentionStep-by-step SQL logic buildingReal-world case studiesAI and analytics preparation focus", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/9/79/818/516/9798185163009_b.jpg", "price_data" : { "retail_price" : "18.00", "online_price" : "18.00", "our_price" : "18.00", "club_price" : "18.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
SQL Mastery Series for AI, Data Science & Modern Computing|Uthayasooriya Amarasena

SQL Mastery Series for AI, Data Science & Modern Computing : Volume 2: SQL Querying and Data Manipulation Mastery Through Story

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Overview

The journey of this volume began with a simple but profound vision: to empower learners to move beyond memorizing commands and instead think with SQL - to see queries not as isolated instructions, but as tools for intelligent analysis, structured reasoning, and real-world problem solving.
In the early chapters, the learner was introduced to basic retrieval and filtering, the essential grammar of databases. Gradually, these skills expanded into aggregation, joins, and optimization, mirroring the natural progression from curiosity to mastery. Each section was carefully designed to build confidence, ensuring that learners could not only write queries but also interpret, refine, and apply them in diverse contexts.
The applied labs - spanning healthcare, retail, education, and AI workflows - were chosen deliberately. They demonstrate how SQL is not confined to classrooms or textbooks, but is a living language of data that powers patient dashboards, revenue reports, student progress trackers, and machine learning pipelines. By embedding these scenarios, the book bridges theory with practice, preparing learners for professional challenges.
Queries are not presented as rote formulas, but as logical expressions of thought. Learners are encouraged to ask: Why does this query work? How does it scale? What insight does it reveal? In answering these questions, they cultivate a mindset that transcends syntax and embraces analysis. Finally, the self-assessment sections and mini projects ensure that learning is active, reflective, and integrative. By testing theory, solving practical challenges, and designing small systems, learners consolidate their skills and prepare for the transition into Volume 3, where database design, advanced optimization, and AI-driven analytics await.
This book is written with gratitude - to the mentors who shaped its philosophy, the colleagues who refined its clarity, the learners whose curiosity inspired its pedagogy, and the communities whose real-world challenges gave it relevance. May it serve as both a guide and companion on the learner's journey from basic queries to intelligent analysis, and onward to the design of robust, ethical, and future-ready data systems.
Teaching Philosophy of This Volume
This volume transforms the learner from a beginner who knows basic SQL syntax into a confident data explorer capable of retrieving, filtering, manipulating, and summarizing information from real-world databases.
Learning Style

  • Storytelling-based explanations
  • Mnemonics for rapid memory retention
  • Step-by-step SQL logic building
  • Real-world case studies
  • AI and analytics preparation focus

This item is Non-Returnable

Details

  • ISBN-13: 9798185163009
  • ISBN-10: 9798185163009
  • Publisher: Independently Published
  • Publish Date: July 2026
  • Dimensions: 9 x 6 x 0.81 inches
  • Shipping Weight: 1.16 pounds
  • Page Count: 394

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