Understanding Data: Navigating Statistics, Science, and AI
Description
Understanding Data: Navigating Statistics, Data, and AI equips you with the knowledge to engage with data from a more nuanced perspective and increase your impact as a decision-maker in an increasingly data-driven world.
Throughout this three-course series, develop essential data literacy skills to navigate claims about data, statistics, science, and artificial intelligence – with no math or programming required. Learn to evaluate statistics used in places like headlines, advertisements, and research to increase your critical thinking skills and deepen your understanding of how scientific research can be misunderstood and misinterpreted. By exploring the recent rise in artificial intelligence (AI), you’ll also learn to engage critically with current narratives regarding data and AI.
At the end of this three-course series, you’ll be able to engage with data from a more critical perspective, integrate data and statistics into papers, reports, or stories, and actively support your perspectives with quality data and information.
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Subject
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Language
English
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Duration
12 weeks
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Status
Available
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U-M Credit Eligible
No
Instructor
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Elle O'Brien
Lecturer IV and Research Investigator
University of Michigan, School of Information
Courses (3)
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Learn moreHow to Describe Data
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4 weeks
How to Describe Data examines the use of data in our everyday lives, giving you the ability to assess the usefulness and relevance of the information you encounter. In this course, learn about uncerta -
Learn moreHow Science Turns Data Into Knowledge
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4 weeks
How Science Turns Data Into Knowledge teaches you how to evaluate scientific claims critically, address experimental limitations, and recognize the roles of trust and responsibility within research. D -
Learn moreDecoding AI: A Deep Dive into AI Models and Predictions
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4 weeks
Decoding AI: A Deep Dive into AI Models and Predictions explores the significance of large datasets, demystifies generative artificial intelligence (AI), and challenges common media myths about AI. By
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