In this course, we will explore different types of problems, the boundaries of what makes a problem solvable, and the different algorithms, rules, and heuristics we can implement to solve these problems.
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课程信息
您将学到的内容有
Ascribe human and computational problems to various definitions of difficulty and problem solving techniques.
Use problem solving strategies to break down problems.
Describe the effects of various sources of bias in judgement and decision making.
Analyze and apply heuristic models and probability modeling to a variety of decision making scenarios.
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科罗拉多大学波德分校
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授课大纲 - 您将从这门课程中学到什么
Problems for Minds and Machines
This week we will begin our discussions by defining the boundaries and limitations of problems and their solutions.
Computers and Logic
This week we will explore adapting problem-solving approaches into computational methods.
Humans and Heuristics
This week we will discuss judgment and decision making as a different kind of problem-solving and explore how heuristics are used for these tasks.
Course Assessment & Wrap-Up Discussion
In this module, you will test your knowledge on methods for solving problems.
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- 5 stars57.48%
- 4 stars30.70%
- 3 stars8.66%
- 2 stars1.57%
- 1 star1.57%
来自METHODS FOR SOLVING PROBLEMS的热门评论
Some of the resources are broken. Also, there are some quizzes which require revision
Increased my critical thinking and decision making.
it really broaden the way i look and attempt problems
A beautiful introductory course that introduces to the methods of solving and reasoning behind them.
关于 Mind and Machine 专项课程
This specialization examines the ways in which our current understanding of human thinking is both illuminated and challenged by the evolving techniques and ideas of artificial intelligence and computer science. Our collective understanding of “minds” – both biological and computational – has been revolutionized over the past half-century by themes originating in fields like cognitive psychology, machine learning, neuroscience, evolutionary psychology, and game theory, among others. This specialization focuses on both the larger “historical” arc of these changes as well as current research directions and controversies.

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