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 defining key terms and exploring how systems “learn” from data, you will gain a baseline understanding of how AI works. Work to understand different critiques of AI narratives, learn to navigate conversations with precision, discern conflicts of interest, and appreciate the multidisciplinary expertise needed to shape AI's impact on society. This course provides you with the strategies and frameworks to engage in better conversation about the role of AI in your work and beyond.
Decoding AI: A Deep Dive into AI Models and Predictions
This course is part of Understanding Data: Navigating Statistics, Science, and AI Specialization
Instructor: Elle O'Brien
Sponsored by Coursera Learning Team
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What you'll learn
Learn key concepts and terminology in artificial intelligence (AI), including machine learning, generative AI, and deep learning
Learn the core components of machine learning systems, including data, models, and evaluation techniques
Recognize why AI systems can fail and identify the kinds of work required to make useful technology
Identify common pitfalls in conversations about AI and recognize conflicts of interest when interpreting claims about AI systems
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There are 4 modules in this course
What's included
7 videos5 readings1 assignment1 discussion prompt
What's included
6 videos2 readings1 assignment
What's included
5 videos2 readings1 assignment
What's included
5 videos3 readings2 assignments1 discussion prompt
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