Artificial Intelligence

开始时间: 待定 持续时间: 12 weeks

所在平台: edX

课程类别: 计算机科学

大学或机构: UC BerkeleyX(加州大学伯克利分校)

授课老师: Pieter Abbeel Dan Klein

   

课程主页: https://www.edx.org/course/artificial-intelligence-uc-berkeleyx-cs188-1x

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课程评论: 6 个评论

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课程详情

*Note - This is an Archived course*

Artificial intelligence is already all around you, from web search to video games. AI methods plan your driving directions, filter your spam, and focus your cameras on faces. AI lets you guide your phone with your voice and read foreign newspapers in English. Beyond today's applications, AI is at the core of many new technologies that will shape our future. From self-driving cars to household robots, advancements in AI help transform science fiction into real systems.

The course will introduce the basic ideas and techniques underlying the design of intelligent computer systems. CS188.1x focuses on Behavior from Computation and will cover the following areas:

  • Statistical and decision–theoretic modeling paradigm. By the end of this course, you will have built autonomous agents that efficiently make decisions in stochastic and in adversarial settings.
  • Reasoning and Learning. With this additional machinery your agents will be able to draw inferences in uncertain environments and optimize actions for arbitrary reward structures. Your machine learning algorithms will classify handwritten digits and photographs.
  • Applications for a wide variety of artificial intelligence problems. The techniques you learn in CS188x will serve as the foundation for further study in any application area you choose to pursue.

Join us today to learn more about how AI affects your life, and where it is headed in the future.


This is a past/archived course. At this time, you can only explore this course in a self-paced fashion. Certain features of this course may not be active, but many people enjoy watching the videos and working with the materials. Make sure to check for reruns of this course.

课程大纲

  • Basic ideas and techniques underlying the design of intelligent computer systems
  • Statistical and decision–theoretic modeling paradigm
  • How to build agents that exhibit reasoning and learning
  • Applications for a wide variety of artificial intelligence problems

课程评论(6条)

0

王鹏_D 2013-07-08 00:12 0 票支持; 0 票反对

在这个链接:https://courses.edx.org/courses/BerkeleyX/CS188.1x/2012_Fall。可以注册和查看2012年秋季的课程包。不知对比2013春季课程有什么不同。

-1

X-猪 2013-05-26 23:05 0 票支持; 1 票反对

兄弟们这个课现在好像不能再注册了?还有哪里能看吗?

1

蒋勇NLP 2013-05-25 19:27 1 票支持; 0 票反对

作为对AI感兴趣的非CS童鞋,这门课让我深深爱上了CS,蛋蛋老师讲课相当有激,他是我见过第二个讲课这么有激情的老师(第一个是哈弗CS50计算机科学导论的 Malan),课程的Quiz非常赞,PA是实现有趣游戏的一些算法,通过cs188.1x全部的学习就可以完成一个自动吃豆子(Pac-Man)的游戏。这门课也是berkeley的cs188课程的上半部分Planning,下半部分是机器学习,非常期待,但是老师说明年年初才能上线。。略伤心ing

1

wzyer 2013-05-22 15:31 1 票支持; 0 票反对

这门课我会给每一个想学AI的人推荐。编程作业灰常灰常有意思,作业和考试题目切中要点,PPT里还有那么多超级有爱的机器人。相当期待下半部分。

1

某李的技术博客 2013-05-21 20:04 1 票支持; 0 票反对

接上。我把最后一次编程作业(Q学习)做了个录像,后面pacman学习结束后相当生猛。http://v.youku.com/v_show/id_XNTQ2MjA4NzU2.html

3. adversarial search
确定:Minimax搜索,评价函数,阿尔法-贝塔修剪
不确定:Expectimax搜索,效用,偏好,理性偏好

4. MDP(马尔科夫决策过程)
MDP定义,时间限制价值(time limited value),政策,Q-值,价值迭代,最优政策,贝尔曼方程,政策评估,政策迭代,离线计划,在线计划。

5. 强化学习
有模型学习,无模型学习,Temporal Difference学习,Q-学习,Exploration VS Exploitation, 特征,线性回归

1

某李的技术博客 2013-05-21 20:02 1 票支持; 0 票反对

这门课内容非常充实,是伯克利本科高年级/研究生低年级课程的上半部分(下半部分2014年推出,只对学过上半部分的学生开放),虽是入门课,但却并不肤浅,不得不说该校教育质量很高。授课老师为Dan Klein,他是自然语言处理领域的专家。课程比较有趣,编程作业基本围绕吃豆子游戏展开很有成就感,问答题对理解基本概念帮助很大,准备非常详实。虽然具有趣味性,美中不足的是Dan的讲解略显啰嗦,所以比起Cousera的NLP,这门课我不得不花更多时间。

基本课程内容如下(有些内容不知道怎么翻译就用课程原名了,见谅):
第一部分. 计划。
1.搜索
uninformed search:广搜,深搜
informed search : heuristic,consistency VS admissibility, 贪心搜索,uniform cost搜索,A*图搜索,A*树搜索

2. CSP(约束满足问题)
回溯搜索
过滤:向前检查,约束扩张,arc consistency, k-consistency
顺序:MRV,LCV,cutset, 树状CSP

Deep Learning Specialization on Coursera

课程简介

UC Berkeley's upper division course CS188: Introduction to Artificial Intelligence now available to everyone online.
 
"Nothing short of awesome. This is a top-notch class that teaches you a lot of important concepts in optimization and AI, while making you feel like you're on a wonderful adventure of discovery and fun." edX student review

课程标签

AI 人工智能 人工智能导论 人工智能入门 Dan-Klein 机器学习

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