Data science analytics decision de mun johnathan (5 resultados)
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 67,72
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
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EUR 75,70
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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 71,19
Envío por EUR 6,85Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 96,00
Envío por EUR 64,05Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Taschenbuch. Condición: Neu. Neuware - This comprehensive graduate-level course develops students into analytically fluent, AI-powered quantitative business decision-makers. Spanning the full analytics spectrum from probability theory, hypothesis testing, and foundational statistical modeling through advanced concepts with machi…ne learning, generative AI, and intelligent automation, students build theoretical and practical competence in applying data science methods to genuine business problems. The course moves from understanding data structures and relationships, through Exploratory Data Analysis, parametric and nonparametric methods, and the full range of exotic regression techniques (Elastic, Lasso, Logistic, Nonlinear, Partial Least Squares, Poisson, Stepwise), to prediction, AI classification (Cluster, Ensemble, KNN, Neural Network, SVM), time-series forecasting (ARIMAX, GARCH), prescriptive optimization, and causal inference with experimental design. Throughout the course, modern AI tools such as Julius AI and ChatGPT serve as practical accelerators for analysis, visualization, and communication. At the same time, students engage in generative AI architecture and prompting, natural language processing, and agentic AI systems, while continuing to work on analytical software applications (Risk Simulator, BizStats, R-Studio, Power BI). The emphasis at every stage is on analytical judgment-knowing which method to apply, how to evaluate its outputs critically, how to recognize its limitations, and how to translate findings into defensible strategic recommendations for executive audiences. The course culminates in AI ethics, governance, and strategic decision-making, equipping students with both rigorous analytical foundations and a practical AI-powered toolkit to translate raw data into responsible, actionable business intelligence. No prior programming experience required; tool fluency, analytical reasoning, and managerial judgment are the core competencies developed.
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- Impresión bajo demanda
Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 76,92
Envío por EUR 43,18Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. This comprehensive graduate-level course develops students into analytically fluent, AI-powered quantitative business decision-makers. Spanning the full analytics spectrum from probability theory, hypothesis testing, and foundational statistical modeling through advanced concepts with machin…e learning, generative AI, and intelligent automation, students build theoretical and practical competence in applying data science methods to genuine business problems. The course moves from understanding data structures and relationships, through Exploratory Data Analysis, parametric and nonparametric methods, and the full range of exotic regression techniques (Elastic, Lasso, Logistic, Nonlinear, Partial Least Squares, Poisson, Stepwise), to prediction, AI classification (Cluster, Ensemble, KNN, Neural Network, SVM), time-series forecasting (ARIMAX, GARCH), prescriptive optimization, and causal inference with experimental design. Throughout the course, modern AI tools such as Julius AI and ChatGPT serve as practical accelerators for analysis, visualization, and communication. At the same time, students engage in generative AI architecture and prompting, natural language processing, and agentic AI systems, while continuing to work on analytical software applications (Risk Simulator, BizStats, R-Studio, Power BI). The emphasis at every stage is on analytical judgment-knowing which method to apply, how to evaluate its outputs critically, how to recognize its limitations, and how to translate findings into defensible strategic recommendations for executive audiences. The course culminates in AI ethics, governance, and strategic decision-making, equipping students with both rigorous analytical foundations and a practical AI-powered toolkit to translate raw data into responsible, actionable business intelligence. No prior programming experience required; tool fluency, analytical reasoning, and managerial judgment are the core competencies developed. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
