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AI and Data Literacy
Overview
This entry-level text introduces foundational concepts in data, machine learning, visualization, and responsible AI. It develops practical skills for evaluating AI-generated outputs, understanding data quality, and using modern AI tools effectively and ethically. The material is presented in a clear, accessible manner, making it suitable for learners from any background and supporting rapid adoption of essential AI literacy across disciplines.
Courses Used In
AI Literacy, Data Science Foundations, Computer Science Principles, Digital Literacy, General Education AI/Data Literacy, Introduction to Data Science (non-majors), Information Systems, Business Analytics Foundations, Educational Technology survey courses
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- eText ISBN: 978-1-969233-43-2 Use for college bookstore order
- Print ISBN: 978-1-969233-37-1 Click to purchase
Data Mining and Exploration
Overview
This entry-level text introduces the core methods used to discover patterns, relationships, and insights in modern datasets. Topics include descriptive statistics, data exploration, preprocessing, clustering, classification, association analysis, and AI-enhanced techniques for working with text, images, and complex data. The content is designed to support learners from any discipline, providing a practical and accessible foundation in data mining and the role of AI throughout the analytical process.
Courses Used In
Data Mining Foundations, Data Analytics, CTE IT/Data Pathway, Advanced Business Analytics electives,
Introduction to Data Mining, Applied Data Analytics, Business Analytics, Information Systems Analytics, Machine Learning Survey (non-majors)
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- eText ISBN: 978-1-969233-45-6 Use for college bookstore order
- Print ISBN: 978-1-969233-38-8 Click to purchase
Machine Learning and Natural Language Processing
Overview
This text introduces the core concepts and practical workflows behind modern machine learning and natural language processing. While prior coursework in AI and Data Literacy or Data Mining and Exploration is recommended, it is not required. Topics include supervised and unsupervised learning, model evaluation, recommendation systems, optimization, text preprocessing, embeddings, sentiment analysis, topic modeling, and applied NLP pipelines. The material emphasizes clarity and real-world application, helping learners understand how ML and NLP models are developed, evaluated, and applied in business and industry contexts.
Courses Used In
Applied Machine Learning, AI Foundations, Data Analytics, CTE IT/Data Pathway electives,
Introduction to Machine Learning (non-majors), Applied Machine Learning for Business, NLP Foundations, Information Systems Analytics
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eText ISBN: 978-1-969233-46-3 Use for college bookstore order
Print ISBN: 978-1-969233-39-5 Click to purchase
Introduction to Business Analytics
Overview
This text provides a clear, practical foundation in how organizations use data to understand performance, diagnose problems, forecast outcomes, and recommend data-driven actions. It covers descriptive, diagnostic, predictive, and prescriptive analytics, along with forecasting, basic modeling, dashboards, and communication of results. The writing emphasizes clarity and practical insight, helping learners build strong analytical thinking and interpretation skills.
Courses Used In
Business Analytics, Data Analytics Foundations, CTE Business/Finance, Marketing Analytics, Introduction to Business,Introduction to Business Analytics, Data Analytics for Business, Information Systems, Business Intelligence, Decision Support/Management
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- eText ISBN: 978-1-969233-47-0 Use for college bookstore order
- Print ISBN: 978-1-969233-40-1 Click to purchase
Programming for Analytics
Overview
This text introduces the practical coding skills required for modern data work. It covers the role of programming in analytics, reproducibility and automation, fundamentals of R and Python, data structures, functions, libraries, debugging, and AI-assisted coding. Concepts are presented clearly to support reliable, repeatable analysis without assuming prior programming experience.
Courses Used In
Introduction to Programming for Data, Python for Data, R for Data, Data Analytics Foundations, CTE IT/Data Pathway,Programming for Analytics, Introduction to R/Python for Data, Applied Data Analytics, Information Systems Analytics
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- eText ISBN: 978-1-969233-48-7 Use for college bookstore order
- Print ISBN: 978-1-969233-41-8 Click to purchase
Data Wrangling with SQL
Overview
This text teaches how to clean, structure, and prepare real-world data using SQL. Topics include data profiling, handling messy values, joins and merges, filtering, derived fields, reshaping tables, and maintaining data quality at scale. The focus is on practical skills that transform raw data into reliable, analysis-ready datasets.
Courses Used In
SQL for Data, Data Wrangling Foundations, Introduction to Databases, CTE IT/Data Pathway,SQL for Analytics, Data Wrangling, Applied Data Preparation, Information Systems Analytics
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- eText ISBN: 978-1-969233-44-9 Use for college bookstore order
- Print ISBN: 978-1-969233-42-5 Click to purchase