Data analytics curriculum data analytics curriculum (8 Ergebnisse)

Zustand: As New. Unread book in perfect condition.

Zustand: As New. Unread book in perfect condition.

Taschenbuch. Zustand: Neu. Neuware - Simple, easy intro to data mining hands on for beginners.This hands-on workbook uses Orange, a powerful visual data-mining tool built on Python, to guide you through clustering, classification, and association techniques. With drag-and-drop workflows and intuitive widgets, you'll explore, clean, and model data step-by-step-no programming required.Perfect for beginners, students, and instructors, these structured labs make complex analytics approachable and fun, building real-world skills that translate directly into data science careers. Orange turns data mining into an engaging, visual learning experience-ideal for anyone ready to get started.…

Taschenbuch. Zustand: Neu. Neuware.

Taschenbuch. Zustand: Neu. Neuware.

Taschenbuch. Zustand: Neu. Neuware - Jumpstart your journey into data with this clear, approachable introduction designed for absolute beginners. Whether you're a student, educator, or curious career-changer, this book walks you through essential concepts-from wrangling data and reading charts to understanding AI, ethics, and career paths-using real-world examples and plain language.Pair this book with companion books with lab exercises to practice (available in R and Orange), slides, solution guides and more available resources at our website to bring your learning data analytics to life.…

Taschenbuch. Zustand: Neu. Neuware - Programming for Analytics 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 thinking, 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 or independent study. Resources for learning are available from the publisher.…

Taschenbuch. Zustand: Neu. Neuware.