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时间:2020-07-27 作者:燕大留学 【原创】 阅读 为配合学校“双一流”建设,培养具有国际视野和国际竞争力的高素质人才,2020年我校拟开展美国哈佛大学暑期在线课程学习项目。具体通知如下: 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。 项目介绍 (一)哈佛大学“领导力与企业管理”在线课程项目 1 . 在线课程简介: Managing a business today is fundamentally different than it was just 30 years ago. The most profound differences we’ve come to believe, is the level of complexity people have to cope with. Complex systems have always existed, of course—and business life has always featured the unpredictable, the surprising, and the unexpected. But complexity has gone from something found mainly in large systems, such as elitism to something that affects almost everything we touch: the products we design, the job we do every day, and the organization we oversee. Most of this in crease has resulted from the information technology revolution of the past few interconnected and interdependent, which means that they are, by definition, more complex. Complicated system have many moving parts, but they operate in patterned ways. The electrical grid that powers the light is complicated: There are many possible interactions within its but they usually follow a pattern. It’s possible to make accurate predictions about how a complicated system will behave. For instance, flying a commercial airplane involves complicated but predicated steps, and as a result it’s astonishingly safe. Implementing s Six Sigma process can be complicated, but the inputs, practices, and outputs are relatively easy to predict. 2 . 课程主要内容: Types of Business Challenges Difference between knowing and thinking Evolution of Management and Leadership Leadership and the neuroscience of decision making Skills for a complex world: Taming ADT Leadership and Teaming Skills for a complex world: Increasing mindfulness …… 3 . 课程主要安排: 课程:企业管理/领导力 授课导师:哈佛大学教授 形式:Zoom(含课前文献阅读+文献综述+教授集中教学+线下作业+小组汇报) 总课时:30课时,其中教授16个课时(每课时45分钟) 课程时间:2020年8月3日-8月15日 4 . 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。 其他方面收获: 1. 提升稀缺竞争力,助力国内外名校申请:通过学分项目课程的学习和研究,帮助每一位项目同学提高科研和科学素养能力,认识名校课程教授。 2. 获得全球硕士/博士奖学金招生信息:项目结束后,项目方会邀请所有项目同学进入“招生信息群”会定时发布全球高校教授招生信息。 5 . 项目费用 (1)费用标准:8000元人民币 (2)费用说明:包括项目课程费用6167元、杂费119美元及项目管理费1000元。 (3)对于课程合格成绩优秀的学生有大额资助(详情可见燕大官网通知) (二)哈佛大学“人工智能与机器人”在线课程项目 1 . 在线课程简介: AI is an important technology that supports daily social life and economic activities. 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. 2 . 在线课程主要内容: 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 …… 3 . 在线课程主要安排: 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,其中教授课时16、博士课时3(每课时45分钟) 教授实时教学时间:2020年8月13日-8月25日 (1)课前文献材料阅读、文献综述写作培训; (2)小组讨论:学员将被分为不同的小组完成课程前文献综述的写作及课后讨论; (3)在线课程相关准备工作; (4)在线课程、学术讲座; (5)线下作业; (6)小组汇报及结业评比; 4 . 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。 其他方面收获: (1)提升稀缺竞争力,助力国内外名校申请:通过学分项目课程的学习和研究,帮助每一位项目同学提高科研和科学素养能力,认识名校课程教授。 (2)获得全球硕士/博士奖学金招生信息:项目结束后,项目方会邀请所有项目同学进入“招生信息群”会定时发布全球高校教授招生信息。 5 . 项目费用 (1)费用标准:8500元人民币 (2)费用说明:包括项目课程费用6667元、杂费119美元及项目管理费1000元。 (3)对于课程合格成绩优秀的学生有大额资助(详情可见燕大官网通知) 报名条件和方式 1 . 我校全日制在读本科生/研究生; 2 . 具有一定外语水平,通过项目方内部面试。 报名方式: 1 . 有意向者请于2020年8月1日之前将《燕山大学线上项目申请表》和《线上项目学生家长声明》电子版发送至 expert@ysu.edu.cn ; 2 . 报名成功后,项目方将安排视频面试,面试通过后缴纳项目课程费用; 3 . 申请者通过项目面试、学术审核以及我校的资格审核后,确定预录取名单; 4 . 申请者提交正式申请材料并缴纳项目费用,获得学校录取后参加在线学习; 5 . 课程结束并且通过课程考核的学员,学校将资助经费拨付至本人账户。 6 . 报名截止时间:2020年8月1日 招生名额:每个项目各20人 项目咨询 项目方负责人付老师:手机13265306036 微信号:fj911726520 校内联系人:薛老师:微信同手机13333311867座机:0335-8074583 校内联系人:王老师:微信同手机18833981251 点击联系薛老师 点击联系王老师 |