Starting Data Analytics with Generative AI and Python

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Bol From the Back Cover Generative AI for Data Analytics is a guide to enhancing and accelerating data analytics using ChatGPT. This book walks you through the full analytics pipeline, demonstrating the discipline’s core tools and methods with an easy-to-understand e-commerce example. For each step in the process, you’ll discover how ChatGPT can implement data techniques from simple plain-English prompts. Written by a pair of world-class data scientists and an experienced risk manager, the book concentrates on the practical analytics tasks you'll do every day. Each topic is illustrated with transcripts of authentic ChatGPT conversations, showing best practice prompt engineering in action. You'll rapidly realize ChatGPT's potential and learn how and when to apply it appropriately. The book provides vital guidance on the model’s risks and mistakes so you can make the most of its capabilities without being blindsided by its shortcomings. About the reader Whether you're a data expert seeking efficiency gains, an analyst looking to extend your spreadsheets with serious data tools, or a complete beginner making a ChatGPT-empowered career jump, this book is for you. Combine the best of human data analysis with the power of AI and ChatGPT. Generative AI for Data Analytics teaches you how to accelerate essential data analytics tasks using ChatGPT. You'll learn how to: Write great prompts for ChatGPT Perform end-to-end descriptive analytics Set up an AI-friendly data analytics environment Evaluate the quality of your data Developing a strategic analysis plan Generate code to analyze non-text data Explore text data directly with ChatGPT Prepare reliable reports About the technology Generative Pre-trained Transformer (GPT) AI models like ChatGPT can turbocharge your analytical workflow by generating insights in minutes that might otherwise take hours or days of work and research. A data analyst can use ChatGPT for a huge variety of tasks, including planning and designing analyses, generating code-based solutions, and selecting statistical tools.

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From the Back Cover Generative AI for Data Analytics is a guide to enhancing and accelerating data analytics using ChatGPT. This book walks you through the full analytics pipeline, demonstrating the discipline’s core tools and methods with an easy-to-understand e-commerce example. For each step in the process, you’ll discover how ChatGPT can implement data techniques from simple plain-English prompts. Written by a pair of world-class data scientists and an experienced risk manager, the book concentrates on the practical analytics tasks you'll do every day. Each topic is illustrated with transcripts of authentic ChatGPT conversations, showing best practice prompt engineering in action. You'll rapidly realize ChatGPT's potential and learn how and when to apply it appropriately. The book provides vital guidance on the model’s risks and mistakes so you can make the most of its capabilities without being blindsided by its shortcomings. About the reader Whether you're a data expert seeking efficiency gains, an analyst looking to extend your spreadsheets with serious data tools, or a complete beginner making a ChatGPT-empowered career jump, this book is for you. Combine the best of human data analysis with the power of AI and ChatGPT. Generative AI for Data Analytics teaches you how to accelerate essential data analytics tasks using ChatGPT. You'll learn how to: Write great prompts for ChatGPT Perform end-to-end descriptive analytics Set up an AI-friendly data analytics environment Evaluate the quality of your data Developing a strategic analysis plan Generate code to analyze non-text data Explore text data directly with ChatGPT Prepare reliable reports About the technology Generative Pre-trained Transformer (GPT) AI models like ChatGPT can turbocharge your analytical workflow by generating insights in minutes that might otherwise take hours or days of work and research. A data analyst can use ChatGPT for a huge variety of tasks, including planning and designing analyses, generating code-based solutions, and selecting statistical tools.


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  • 9781633437210
  • 9781638356424
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