ワシントン大学（University of Washington） による Designing Autonomous AI の受講者のレビューおよびフィードバック
When children learn how to hit a baseball, they don’t start with fastballs. Their coaches begin with the basics: how to grip the handle of the bat, where to put their feet and how to keep their eyes on the ball. Similarly, an autonomous AI system needs a subject matter expert (SME) to break a complex process or problem into easier tasks that give the AI important clues about how to find a solution faster.
In this course, you’ll learn how to distill a business challenge into its component parts by creating an autonomous AI design plan. Using lessons, goal setting, skills, strategies and rewards, you’ll incorporate your SME’s knowledge directly into your AI’s “brain,” the agent that powers your autonomous system. You'll learn when and how to combine various AI architecture design patterns, as well as how to design an advanced AI at the architectural level without worrying about the implementation of neural networks or machine learning algorithms.
At the end of this course, you’ll be able to:
• Interview SMEs to extract their unique knowledge about a system or process
• Combine reinforcement learning with expert rules, optimization and mathematical calculations in an AI brain
• Design an autonomous AI brain from modular components to guide the learning process for a particular task
•. Validate your brain design against existing expertise and techniques for solving problems
• Produce a detailed specifications document so that someone else can build your AI brain
This course is part of a specialization called Autonomous AI for Industry, which will launch in fall 2022....