一、学校简介

哈佛大学在文学、医学、法学、商学等多个领域拥有崇高的学术地位及广泛的影响力，被公认为是当今世界最顶尖的高等教育及研究机构之一。与此同时，该校还负责管理运行哈佛-史密松森天体物理中心、麻省总医院、波士顿儿童医院等机构。

截止至2019年10月，哈佛大学共培养了包括富兰克林·罗斯福、贝拉克·奥巴马在内的8位美利坚合众国总统，而哈佛的校友、教授及研究人员中共产生了160位诺贝尔奖得主（世界第一）、18位菲尔兹奖得主（世界第一）、14位图灵奖得主（世界第四）。

2019-20年，哈佛大学位列软科世界大学学术排名世界第一、USNews世界大学排名世界第一、QS世界大学排名世界第三、泰晤士高等教育世界大学排名世界第七；泰晤士高等教育世界大学声誉排名世界第一。

二、课程简介

AI is an important technology that supports daily social life and economic activities. It contributes greatly to the sustainable growth of Japan’s economy and solves various social problems. In recent years, AI has attracted attention as a key for growth in developed countries such as Europe and the United States and developing countries.  The attention has been focused mainly on developing new artificial intelligence information communication technology(ICT) and robot technology(RT). Although recently developed AI technology certainly excels in extracting certain patterns, there are many limitations. Most ICT models are overly dependent on big data, lack a self-idea function, and are complicated.  During the class, rather than merely developing next-generation artificial intelligence technology, we aim to develop a new concept of general-purpose intelligence cognition technology.  

Recent advance in neuroimaging provide tools to measure structure and map functional networks in the human brain, albeit with limitations inherent to safe, non-invasive approaches.  The low participant burden of these techniques makes them particularly well suited for large, high- throughput studies.  Taking advance of these innovation, the Brain Genomics Superstruct project(GSP)was initiated to yield a dates of structural, functional, behavioral, and genetic information on a large-scale data collection efforts.  The dataset is intended to allow exploration of normative properties of brain structure and function, and link individual difference to behavioral phenotypes and genetic origins.  The present data descriptor manuscript details the initial release of structural, functional, and behavioral measures.

三、主要内容

Machine Learning & AI Definitions

Natural Neurons

Natural Intelligence

Consciousness

The Human Brain

Connectomics

The Artificial Neuron

Neural Networks

Types of ML

Machine Intelligence

Touring Test

AI, Machine Learning and Computation Design

AI in Pharmaceuticals

AI in Healthcare

AI and Machine Learning in the Insurance Industry

四、教学安排

学科：人工智能

授课导师：哈佛大学/麻省理工学院教授、麻省理工学院博士生

形式：Zoom(含课前文献阅读+文献综述+教授集中教学+博士学术讲座+线下作业+小组汇报)

总课时：35课时，其中教授16个课时、学术讲座6个课时（每课时45分钟）

课程时间：2020年8月13日-8月25日

学习计划：(暂定)

五、项目费用

项目费： 9900元人民币

资助情况：本项目可申请学校奖学金资助500元-1000元

（资助在获得结业合格证明后下学期核发）

六、项目收获

项目结业证书、成绩单、优秀学员证明、美方推荐信、表现优秀者后期可以获得教授推荐信

七、报名及咨询方式

1.全校海外实习名额：20人，请打开预报名链接：https://jinshuju.net/f/2nu4s4，

在线提交意向报名表。报名截止时间7月15日，择优录取，额满为止。

2.咨询电话：0755-26531125/26531127

3.手机/微信：15502014120 赵老师

4.地址：深圳大学留学服务中心（深大小西门右侧二楼）

5.更多项目信息，请扫描下方二维码