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學生對 华盛顿大学 提供的 Machine Teaching for Autonomous AI 的評價和反饋


Just as teachers help students gain new skills, the same is true of artificial intelligence (AI). Machine learning algorithms can adapt and change, much like the learning process itself. Using the machine teaching paradigm, a subject matter expert (SME) can teach AI to improve and optimize a variety of systems and processes. The result is an autonomous AI system. In this course, you’ll learn how automated systems make decisions and how to approach building an AI system that will outperform current capabilities. Since 87% of machine learning systems fail in the proof-concept phase, it’s important you understand how to analyze an existing system and determine whether it’d be a good fit for machine teaching approaches. For your course project, you’ll select an appropriate use case, interview a SME about a process, and then flesh out a story for why and how you might go about building an autonomous AI system. At the end of this course, you’ll be able to: • Describe the concept of machine teaching • Explain the role that SMEs play in training advanced AI • Evaluate the pros and cons of leveraging human expertise in the design of AI systems • Differentiate between automated and autonomous decision-making systems • Describe the limitations of automated systems and humans in real-time decision-making • Select use cases where autonomous AI will outperform both humans and automated systems • Propose an autonomous AI solution to a real-world problem • Validate your design against existing expertise and techniques for solving problems This course is part of a specialization called Autonomous AI for Industry, which will launch in fall 2022....



1 - Machine Teaching for Autonomous AI 的 4 個評論(共 4 個)

創建者 Teresa E


This course teaches you useful AI - how to use the skills of industrial operators to desing Autonomous AI brains that outperforms industrial processes, using Machine Teaching. It is taught using an engaging storytelling technique, full of real world examples where Machine Teaching has been applied to solve high business value problems. By the end of the course, you will know how to select winning use cases and how to apply Machine Teaching to design an Autonomous AI brain for your own use case.

創建者 Heather M


Great first course to understand how to bridge the gap between expert knowledge and the power of reinforcement learning. Looking forward to courses that go deeper into the technology!

創建者 Phil H


Very well structured and paced. Tackles some important topics with real life examples to back it up.

創建者 Syed A S


its full of stories and interviews nothong to lllearn in this course i was expecting the best from university of washington but i am really disapointed after go through the complete course

its full of interviews and stories