Introduction to Artificial Intelligence

Artificial intelligence not only relates to so many high technologies, but also is applied different field such as military, industry, e-market, internet and so on. This course involves not only technologies including intelligence robotics, brain-computer interface, face recognition and so on, but philosophy thinking,such as what is the relation among mind,intelligence and body? So it will inspire you to think a lot of interesting problems related to human beings and society development.

开设学校:哈尔滨工程大学;学科:计算机、

Introduction to Artificial Intelligence课程:前往报名学习

Introduction to Artificial Intelligence视频慕课课程简介:

Artificial intelligence not only relates to so many high technologies, but also is applied different field such as military, industry, e-market, internet and so on. This course involves not only technologies including intelligence robotics, brain-computer interface, face recognition and so on, but philosophy thinking,such as what is the relation among mind,intelligence and body? So it will inspire you to think a lot of interesting problems related to human beings and society development.

前往报名学习

Introduction to Artificial Intelligence课程列表:

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Chapter 1 Introduction

-Chapter 1 Homework

-1.1 Life intelligence and artificial intelligence

--1.1 Life intelligence and artificial intelligence

-1.2 The birth process of artificial Intelligence

--1.2 The birth process of artificial Intelligence

--1.2 The birth process of artificial Intelligence

-1.3 Multidisciplinary crossover artificial intelligence

--1.3 Multidisciplinary crossover artificial intelligence

--1.3 Multidisciplinary crossover artificial intelligence

-1.4 Big data concept

--1.4 Big data concept

--1.4 Big data concept

-1.5 Big data value and cases

--1.5 Big data value and cases

--1.5 Big data value and cases

-1.6 Research and application of artificial intelligence

--1.6 Research and application of artificial intelligence

--1.6 Research and application of artificial intelligence

Chapter 2 Philosophical Basis of AI

-Chapter 2 Homework

-2.1 Artificial intelligence under big history

--2.1 Artificial intelligence under big history

--2.1 Artificial intelligence under big history

-2.2 The philosophical thinking about artificial intelligence

--2.2 The philosophical thinking about artificial intelligence

--2.2 The philosophical thinking about artificial intelligence

-2.3 Artificial intelligence consciousness, mind, body and intelligence

--2.3 Artificial intelligence consciousness, mind, body and intelligence

--2.3 Artificial intelligence consciousness, mind, body and intelligence

-2.4 The rational nature of artificial intelligence

--2.4 The rational nature of artificial intelligence

--2.4 The rational nature of artificial intelligence

Chapter 3 Brain and Neural Science Basis

-Chapter 3 Homework

-3.1 Brain structure and function

--3.1 Brain structure and function

--3.1 Brain structure and function

-3.2 Brain nervous system

--3.2 Brain nervous system

--3.2 Brain nervous system

-3.3 New finds of brain functions

--3.3 New finds of brain functions

--3.3 New finds of brain functions

-3.4 Cognition and intelligence

--3.4 Cognition and intelligence

--3.4 Cognition and intelligence

Chapter 4 Artificial Neural Networks

-Chapter 4 Homework

-4.1 Overview of artificial neural network

--4.1 Overview of artificial neural network

--4.1 Overview of artificial neural network

-4.2 Perceptron and feedforward neural network

--4.2 Perceptron and feedforward neural network

--4.2 Perceptron and feedforward neural network

-4.3 BP algorithm and application

--4.3 BP algorithm and application

--4.3 BP algorithm and application

-4.4 Convolutional neural network

--4.4 Convolutional neural network

--4.4 Convolutional neural network

-4.5 Deep neural network

--4.5 Deep neural network

--4.5 Deep neural network

Chapter 5 Machine Learning

-Chapter 5 Homework

-5.1 Supervised learning

--5.1 Supervised learning

--5.1 Supervised learning

-5.2 Basic theories and methods of deep learning

--5.2 Basic theories and methods of deep learning

--5.2 Basic theories and methods of deep learning

-5.3 Deep learning applications

--5.3 Deep learning applications

--5.3 Deep learning applications

-5.4 Reinforcement learning

--5.4 Reinforcement learning

--5.4 Reinforcement learning

-5.5 Transfer learning

--5.5 Transfer learning

--5.5 Transfer learning

-5.6 Machine game

--5.6 Machine game

--5.6 Machine game

-5.7 Machine art creation

--5.7 Machine art creation

--5.7 Machine art creation

-5.8 Machine intelligent design

--5.8 Machine intelligent design

--5.8 Machine intelligent design

Chapter 6 Sense Intelligence

-Chapter 6 Homework

-6.1 Digital image processing applications

--6.1 Digital image processing applications

--6.1 Digital image processing applications

-6.2 Computer vision

--6.2 Computer vision

--6.2 Computer vision

-6.3 Machine vision

--6.3 Machine vision

--6.3 Machine vision

-6.4 Machine vision applications

--6.4 Machine vision applications

--6.4 Machine vision applications

-6.5 Pattern recognition basics

--6.5 Pattern recognition basics

--6.5 Pattern recognition basics

Chapter 7 Cognition Intelligence

-Chapter 7 Homework

-7.1 Knowledge representation

--7.1 Knowledge representation

--7.1 Knowledge representation

-7.2 Logic and reasoning

--7.2 Logic and reasoning

--7.2 Logic and reasoning

-7.3 Fuzzy reasoning

--7.3 Fuzzy reasoning

--7.3 Fuzzy reasoning

-7.4 Blind search method

--7.4 Blind search method

--7.4 Blind search method

-7.5 Knowledge graph

--7.5 Knowledge graph

--7.5 Knowledge graph

Chapter 8 Language Intelligence

-Chapter 8 Homework

-8.1 General issues in natural language understanding

--8.1 General issues in natural language understanding

--8.1 General issues in natural language understanding

-8.2 Intelligence Q & A

--8.2 Intelligence Q & A

--8.2 Intelligence Q & A

-8.3 Speech recognition basics

--8.3 Speech recognition basics

--8.3 Speech recognition basics

-8.4 Introduction to machine translation

--8.4 Introduction to machine translation

--8.4 Introduction to machine translation

Chapter 9 Robotics

-Chapter 9 Homework

-9.1 Industrial robots

--9.1 Industrial robots

--9.1 Industrial robots

-9.2 Service robots

--9.2 Service robots

--9.2 Service robots

-9.3 Robot vision

--9.3 Robot vision

--9.3 Robot vision

-9.4 Mobile robot synchronous localization and map construction

--9.4 Mobile robot synchronous localization and map construction

--9.4 Mobile robot synchronous localization and map construction

-9.5 Path planning for mobile robots

--9.5 Path planning for mobile robots

--9.5 Path planning for mobile robots

Chapter 10 Hyrbrid Intelligence

-Chapter 10 Homework

-10.1 Basic concepts of hybrid intelligence

--10.1 Basic concepts of hybrid intelligence

--10.1 Basic concepts of hybrid intelligence

-10.2 Brain computer interface

--10.2 Brain computer interface

--10.2 Brain computer interface

-10.3 Wearable technology

--10.3 Wearable technology

--10.3 Wearable technology

-10.4 Exoskeleton technology

--10.4 Exoskeleton technology

--10.4 Exoskeleton technology

Chapter 11 Brain-like Intelligence

-Chapter 11 Homework

-11.1 Brain-like computing

--11.1 Brain-like computing

--11.1 Brain-like computing

-11.2 Artificial brain

--11.2 Artificial brain

--11.2 Artificial brain

Chapter 12 Artificial Intelligence and Society Development

-Chapter 12 Homework

-12.1 From digital manufacturing to intelligent manufacturing

--12.1 From digital manufacturing to intelligent manufacturing

--12.1 From digital manufacturing to intelligent manufacturing

-12.2 Intelligence medical

--12.2 Intelligence medical

--12.2 Intelligence medical

-12.3 Application of artificial intelligence in the military

--12.3 Application of artificial intelligence in the military

--12.3 Application of artificial intelligence in the military

-12.4 Intelligence city

--12.4 Intelligence city

--12.4 Intelligence city

-12.5 Artificial intelligence ethics

--12.5 Artificial intelligence ethics

--12.5 Artificial intelligence ethics

-12.6 Robot ethics

--12.6 Robot ethics

--12.6 Robot ethics

-12.7 Artificial intelligence law

--12.7 Artificial intelligence law

--12.7 Artificial intelligence law

Introduction to Artificial Intelligence开设学校:哈尔滨工程大学

Introduction to Artificial Intelligence授课教师:

莫宏伟-教授-哈尔滨工程大学-

莫宏伟,哈尔滨工程大学自动化学院教授,博士生导师,博士。哈尔滨工程大学自动化学院类脑计算与人工智能研究中心(筹)负责人,哈尔滨工程大学烟台研究院认知智能与海洋信息实验室(筹)负责人。主要研究方向:类脑计算与人工智能、智能机器人与无人机、机器视觉与机器认知、人机融合与混合智能。 2012年获得黑龙江省杰出青年基金资助。承担完成国家自然科学基金、国家重点研发计划、国防预研等项目22项。发表论文80余篇。出版专著6部,授权发明专利7项。 中国人工智能学会自然计算与数字城市专业委员会副主任,中国高校人工智能与大数据联盟常务理事,黑龙江省高等教育学会人工智能教育专业委员会发起人、理事长,黑龙江省生物医学工程学会理事。黑龙江省人工产业联盟副秘书长。黑龙江省人工智能学会前秘书长(2008-2019), “黑龙江省人工智能产业发展推进意见”(2019-2030)核心专家。哈尔滨市新一代人工智能创新发展试验区规划专家组专家。科技部科技项目评议专家。国家自然科学基金委员会评议专家。教育部学位与研究生教育发展中心专家,博士点基金评审专家,福建、广西、河北、北京等多个省地项目评审专家。 第16届中国神经网络大会组委会主席,秘书长。2013ICSI会议主席。担任2017国际生物启发的计算理论与应用(BICTA2017)程序委员会主席以及40多个国际会议程序委员会委员。Research of Information Technology、International Journal of Swarm Intelligence Research、《电子学报》、《数据挖掘》等编委。IEEE Tran on Industrial Informatics 2018 专刊《医疗卫生中的大数据处理》副主编。 担任哈尔滨工程大学世界大学生机器人大赛ROBOCON团队指导教师,哈尔滨工程大学奇点人工智能学生社团创建及指导教师。2005-至今,担任哈尔滨工程大学本科生创新创业实践课程《人工智能理论与技术创新实践》、自动化学院《人工智能导论》、《智能科学与技术导论》、自动化学院研究生专业课《人工智能原理与方法》、硕士留学生课程《人工智能原理与方法》、博士留学生课程《模式识别与智能系统》主讲教师。

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