We live in an age increasingly dominated by algorithms. As machine learning models begin making important decisions based on massive datasets, we need to be aware of their limitations in the real world. Whether it's making loan decisions or re-routing traffic, machine learning models need to accurately reflect our shared values. In this course, we will explore the rise of algorithms, from the most basic to the fully-autonomous, and discuss how to make them more ethically sound.
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Artificial Intelligence Algorithms Models and Limitations
This course is part of Ethics in the Age of AI Specialization
Instructor: Brent Summers
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There are 4 modules in this course
Welcome to the course! We're going to get started with an overview of the course structure as well as an introductory look at the world of algorithms
What's included
5 videos2 readings3 assignments2 discussion prompts
This week, we are going to dive into predictive modeling the core differences in theory and practice
What's included
3 videos2 readings3 assignments1 discussion prompt
This week we are going to focus on machine learning accuracy and training guidelines in the quest for more accurate and ethical models
What's included
3 videos2 readings3 assignments1 discussion prompt
In our final week, we're going to ask some big questions about where all this predictive intelligence leads. We will discuss the trajectory of artificial intelligence and the broader implications for society as well
What's included
4 videos2 readings3 assignments1 discussion prompt
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Google Cloud
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