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AI & Data Literacy

You're reading from AI & Data Literacy

Product type Book

Published in Jul 2023

Publisher Packt

ISBN-13 9781835083505

Pages 238 pages

Edition 1st Edition

Languages

Concepts

Artificial Intelligence

Author (1):

Bill Schmarzo

Table of Contents (14) Chapters

Preface

1. Why AI and Data Literacy?

2. Data and Privacy Awareness

3. Analytics Literacy

4. Understanding How AI Works

5. Making Informed Decisions

6. Prediction and Statistics

7. Value Engineering Competency

8. Ethics of AI Adoption

9. Cultural Empowerment

10. ChatGPT Changes Everything

11. Glossary

12. Other Books You May Enjoy

13. Index

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Qr code Description automatically generated

In the fourth component of the AI & data literacy educational framework, we focus on Prediction and Statistics capabilities. Being prediction and statistics savvy involves leveraging patterns, trends, and relationships uncovered in the organization’s vast data troves to make predictions about what is likely to happen that power more accurate, precision decisions.

A diagram of ethics Description automatically generated with low confidence

Probabilities support the predictions that we make as part of our everyday lives. We watch the news for predictions about tomorrow’s weather. We use GPS to predict how long driving to the movie theater will take. We read columns from sports experts who provide predictions about whether your favorite sports team will win (and will they cover). And it is from the foundation of statistics that we determine the probabilities that help us predict what is likely to happen.Having a solid grasp of statistics goes beyond mere theoretical knowledge...

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Authors (1)

Bill Schmarzo

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.

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