Datajoyai jun 2026 (5 Ergebnisse)
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 67,00
EUR 61,87 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Taschenbuch. Zustand: Neu. Neuware - Introduction to Business Analytics: Student Edition is an accessible, hands-on textbook that introduces students to the concepts, tools, and decision-making processes that drive modern organizations. Written for introductory business analytics, data analytics, and AI literacy courses, the boo…k focuses on practical applications rather than advanced mathematics or programming.Students explore the four major types of analytics-descriptive, diagnostic, predictive, and prescriptive-and learn how organizations use data to improve operations, understand customers, forecast outcomes, and support strategic decisions. Topics include key performance indicators (KPIs), dashboards, data visualization, trend analysis, root cause analysis, forecasting, predictive modeling, classification, artificial intelligence, business communication, and data-driven decision-making.Real-world examples from companies such as Amazon, Netflix, Starbucks, and Walmart demonstrate how analytics creates business value. Hands-on labs and practical exercises help learners apply concepts using realistic business scenarios and modern analytics tools.Designed for community college, undergraduate, workforce training, and business students, this text provides a foundation for future study in business analytics, data science, artificial intelligence, and applied analytics.
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 68,00
EUR 62,56 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Taschenbuch. Zustand: Neu. Neuware - Data Mining and Exploration - Student Edition provides a comprehensive, hands-on introduction to the core methods used in modern data analytics and machine learning. Designed for community college and undergraduate students, this textbook bridges foundational statistical thinking with applied… data mining techniques used in today's AI-driven world.The book begins with the history and evolution of data mining and progresses through essential topics including descriptive statistics, data acquisition, data cleaning, transformation, clustering, classification, and association analysis. Each chapter integrates practical tools such as R, Python environments, and AI-assisted analytics platforms, making abstract concepts accessible through real-world applications.Special emphasis is placed on modern developments in the field, including AI-enhanced data mining, automated feature engineering, natural language processing, and ethical AI practices. Students are guided through structured labs that reinforce learning through hands-on practice and applied problem-solving.Key Features:Full coverage of the data mining pipelineClear explanations of clustering, classification, and association methodsPractical labs and demonstrations in every chapterIntegration of AI tools and modern analytics platformsStrong focus on ethics, bias, and responsible data useDesigned for applied, non-theoretical learners in data science programsThis text is ideal for introductory courses in data mining, data science, business analytics, and AI literacy.
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 68,00
EUR 62,66 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Taschenbuch. Zustand: Neu. Neuware - Machine Learning and Natural Language Processing: Student Edition provides an accessible, applied introduction to machine learning (ML) and natural language processing (NLP) for students, educators, and business professionals. Designed for introductory college courses in analytics, artificial… intelligence, and data science, this text focuses on practical understanding rather than advanced mathematics.Readers learn how machine learning systems identify patterns in data, make predictions, support decision-making, and automate business processes. Topics include supervised and unsupervised learning, classification, regression, recommendation systems, optimization, model evaluation, performance metrics, bias, fairness, and responsible AI practices.The NLP portion of the book explores how computers process and analyze human language. Students learn text preprocessing, tokenization, stopword removal, lemmatization, TF-IDF, word embeddings, sentiment analysis, topic modeling, named entity recognition, conversational AI, text summarization, and generative AI applications.Throughout the text, real-world examples demonstrate how organizations use ML and NLP to improve customer experiences, streamline operations, analyze feedback, and support strategic decisions. Hands-on labs and guided activities help students apply concepts using modern analytics tools and datasets.Written in a clear, student-friendly style, this book bridges the gap between theory and practice while emphasizing ethical considerations, model interpretability, and human oversight. It is ideal for introductory courses in machine learning, artificial intelligence, natural language processing, business analytics, and applied data science.
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 68,00
EUR 62,68 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Taschenbuch. Zustand: Neu. Neuware.
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 69,00
EUR 63,10 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Taschenbuch. Zustand: Neu. Neuware - Programming for Analytics: Student Edition introduces the fundamental programming concepts needed for modern data analytics, business intelligence, artificial intelligence, and data science. Designed for beginners with little or no coding experience, this textbook emphasizes analytical thinki…ng, problem-solving, automation, and reproducible workflows rather than computer science theory.Students learn how programming supports data analysis, automation, reporting, and decision-making. The book introduces core concepts including variables, data types, functions, libraries, data structures, automation, debugging, and reproducibility. Readers explore both R and Python, gaining an understanding of how programming languages support analytics workflows and how skills transfer across platforms.Special attention is given to practical topics that analysts encounter in the workplace, including data manipulation, code organization, reusable functions, automation of repetitive tasks, documentation, debugging strategies, and evaluating code quality. The text also explores the growing role of artificial intelligence as a programming assistant and discusses responsible, ethical, and professional uses of AI-generated code.Hands-on labs, demonstrations, and practice exercises reinforce concepts through realistic analytics scenarios. By focusing on concepts rather than language-specific syntax, this book helps students develop a durable foundation that prepares them for future study in analytics, data science, machine learning, and AI.Ideal for introductory courses in programming for analytics, data analytics, business analytics, artificial intelligence, and data science.
