Bill Schmarzo

AI & Data Literacy (eBook, ePUB)

Empowering Citizens of Data Science

• Format: ePub

Produktbeschreibung

AI is undoubtedly a game-changing tool with immense potential to improve human life.

This book aims to empower you as a Citizen of Data Science, covering the privacy, ethics, and theoretical concepts you'll need to exploit to thrive amid the current and future developments in the AI landscape.

We'll explore AI's inner workings, user intent, and the critical role of the AI utility function while also briefly touching on statistics and prediction to build decision models that leverage AI and data for highly informed, more accurate, and less risky decisions.

Additionally, we'll discuss how organizations of all sizes can leverage AI and data to engineer or create value. We'll establish why economies of learning are more powerful than the economies of scale in a digital-centric world. Ethics and personal/organizational empowerment in the context of AI will also be addressed.

Lastly, we'll delve into ChatGPT and the role of Large Language Models (LLMs), preparing you for the growing importance of Generative AI. By the end of the book, you'll have a deeper understanding of AI and how best to leverage it and thrive alongside it.

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Produktdetails

• Verlag: Packt Publishing
• Seitenzahl: 238
• Erscheinungstermin: 26. Juli 2023
• Englisch
• ISBN-13: 9781835087947
• Artikelnr.: 70032033

Autorenporträt

Bill Schmarzo, The Dean of Big Data is a University of San Francisco School of Management Executive Fellow and an Honorary Professor at the School of Business and Economics at the National University of Ireland-Galway where he teaches and mentors students in his courses "Big Data MBA" and "Thinking Like a Data Scientist". He is the author of Big Data: Understanding How Data Powers Big Business, Big Data MBA: Driving Business Strategies with Data Science, and The Art of Thinking Like a Data Scientist. He has written countless whitepapers, articles and blogs, and given keynote presentations and university lectures on the topics of data science, artificial intelligence/machine learning, data economics, design thinking and team empowerment.