學生對 University of Washington 提供的 Building Autonomous AI 的評價和反饋
Practice makes perfect. It’s true for people learning to master a new skill, and it’s also true for your AI brain. Just as you need the right environment to practice, get feedback and try again, so does your AI brain.
In this course, you’ll solve industrial engineering problems inspired by real problems your instructors have worked on in industry. You’ll learn how to build, test and deploy an AI brain using Microsoft Bonsai, a cloud-based, low-code platform. We’ll walk through the entire Bonsai platform from setup to deployment. Along the way, you’ll use Bonsai to conduct machine teaching experimentation to train a brain and assess its progress. Because you’ll be teaching the brain a relatively complex task, you’ll run multiple simulations until you’re satisfied with the results. You’ll then prep the brain for graduation into the real world — deploying it into a machinery control system or other live environment.
At the end of this course, you’ll be able to:
• Build an autonomous AI that combines reinforcement learning with machine learning, expert rules and other methods that you’ve used in the first two courses of the specialization
• Establish requirements for a simulated environment for your brain to practice a task
• Validate and assess your brain’s performance of a task and make improvements to your brain design
• Evaluate whether a simulator is a good practice environment
• Deploy a brain on a real piece of hardware
This course requires an Azure subscription.
This course is part of a specialization called Autonomous AI for Industry, which will launch in early 2023....