项目背景 Program Background

机器学习(Machine Learning, ML)是一门多领域交叉学科，涉及概*论、统计学、逼近论、凸分析、算法复杂度理论等多门学科。专门研究计算机怎样模拟或实现人类的学习行为，以获取新的知识或技能，重新组织已有的知识结构使之不断改善自身的性能。

它是人工智能的核心，是使计算机具有智能的根本途径，其应用遍及人工智能的各个领域，它主要使用归纳、综合而不是演绎。

Machine Learning (ML) is a multidisciplinary discipline, involving probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory and other disciplines. Specialized in the study of how computers simulate or implement human learning behavior to acquire new knowledge or skills, reorganize the existing knowledge structure to continuously improve its own performance.

It is the core of artificial intelligence, is the fundamental way to make the computer intelligent, its application throughout various fields of artificial intelligence, it mainly uses induction, synthesis rather than deduction.

项目介绍 Program Description

机器学习(Machine Learning, ML)是一门多领域交叉学科，涉及概*论、统计学、逼近论、凸分析、算法复杂度理论等多门学科。专门研究计算机怎样模拟或实现人类的学习行为，以获取新的知识或技能，重新组织已有的知识结构使之不断改善自身的性能。

它是人工智能的核心，是使计算机具有智能的根本途径，其应用遍及人工智能的各个领域，它主要使用归纳、综合而不是演绎。

Machine Learning (ML) is a multidisciplinary discipline, involving probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory and other disciplines. Specialized in the study of how computers simulate or implement human learning behavior to acquire new knowledge or skills, reorganize the existing knowledge structure to continuously improve its own performance.

It is the core of artificial intelligence, is the fundamental way to make the computer intelligent, its application throughout various fields of artificial intelligence, it mainly uses induction, synthesis rather than deduction.

适合人群 Targeting Students

高中生、大学生

计算机科学、通信工程（通讯工程/信息工程）等专业或希望修读相关专业，以及对计算机科学课题感兴趣的学生；具备计算机相关知识的学生优先

High school and college students

Students who major in computer science, communication engineering (Communication engineering/Information Engineering), or wish to study related majors, and are interested in computer science topics; Computer related knowledge is preferred

参考教授 Professor Introduction

Professor Buttery

英国剑桥大学计算机科学与技术学院计算机与语言专业教授

Professor of Computer and Language, School of Computer Science and Technology, University of Cambridge, UK

任职学校 University

剑桥大学（University of Cambridge；勋衔：Cantab），是一所世界**的公立研究型大学，采用书院联邦制，坐落于英国剑桥。其与牛津大学并称为牛剑，与牛津大学、伦敦大学学院、帝国理工学院、伦敦政治经济学院同属“G5超*精英大学”。剑桥大学是英语世界中第二古老的大学，前身是一个于1209年成立的学者协会。

八百多年的校史汇聚了牛顿、开尔文、麦克斯韦、玻尔、玻恩、狄拉克、奥本海默、霍金、达尔文、沃森、克里克、马尔萨斯、马歇尔、凯恩斯、图灵、怀尔斯、华罗庚等科学巨匠，弥尔顿、拜伦、丁尼生、培根、罗素、维特根斯坦等文哲大师，克伦威尔、尼赫鲁、李光耀等政治人物以及罗伯特·沃波尔（*任）在内的15位英国*相。截止2019年10月，共有120位诺贝尔奖得主（世界第二）、11位菲尔兹奖得主（世界第六）、7位图灵奖得主（世界第八）曾在此学习或工作。

剑桥大学在众多领域拥有崇高的学术地位及广泛的影响力，被公认为当今世界***的高等教育机构之一。剑桥大学是英国罗素大学集团、金三角*及剑桥大学医疗伙伴联盟的一员，衍育了科技聚集地“硅沼(Silicon Fen)”。学校共设八座文理博物馆，并有馆藏逾1500万册的图书馆系统及全球*古老的出版社——剑桥大学出版社。

2019-20年度，剑桥大学位居泰晤士高等教育世界大学排名世界第3、QS世界大学排名世界第7、US News世界大学排名世界第9、世界大学学术排名世界第3，泰晤士高等教育世界大学声誉排名世界第4。

University of Cambridge (University of Cambridge; Honours: Cantab) is one of the world's leading public research universities, based in Cambridge, England, with a collegiate system. It is also known as Oxbridge with the University of Oxford, and is one of the "G5 super elite universities" along with the University of Oxford, University College London, Imperial College London and the London School of Economics and Political Science. The University of Cambridge is the second oldest university in the English-speaking world, having grown out of a society of scholars founded in 1209.

The 800-year history of the university has brought together such scientific masters as Newton, Kelvin, Maxwell, Bohr, Born, Dirac, Oppenheimer, Hawking, Darwin, Watson, Crick, Malthus, Marshall, Keynes, Turing, Wiles, Hua Luogen, Milton, Byron, Tennyson, Bacon, Russell, Wittgenstein, and other literary and philosophical masters. Political figures such as Cromwell, Nehru, Lee Kuan Yew and 15 British Prime ministers, including Robert Walpole (the first). As of October 2019, 120 Nobel Prize winners (second in the world), 11 Fields Medal winners (sixth in the world), and 7 Turing Award winners (eighth in the world) have studied or worked here.

The University of Cambridge has a high academic status and extensive influence in many fields, and is recognized as one of the top higher education institutions in the world today. The University of Cambridge is a member of the UK Russell Group of Universities, the Golden Triangle and the Cambridge University Medical Partnership Alliance, and has developed a science and technology gathering place "Silicon Fen". The university is home to eight liberal arts museums, a library system with a collection of more than 15 million volumes and the world's oldest publishing house, Cambridge University Press.

In 2019-20, the University of Cambridge was ranked 3rd in the world by The Times Higher Education World University Rankings, 7th in the world by QS World University Rankings, 9th in the world by US News World University Rankings, 3rd in the world Academic Rankings and 4th in the world by The Times Higher Education World University Reputation Rankings.

项目大纲 Syllabus

• ML的介绍，总体*和例子。An introduction to ML, overall goals and examples.
  

• ML的概*和统计概述 Probabilistic and statistical overview of ML
  

• *大似然估计(MLE)原则，贝叶斯估计，地图。Maximum Likelihood Estimation (MLE) principle, Bayesian estimation, maps.

• 分类概述，非参数K近邻风险*小化，评估分类器。Classification overview, nonparametric K-nearest neighbor risk minimization, evaluation of classifiers.

• 朴素贝叶斯，生成型与判别型 Naive Bayes, generative and discriminative

• 线性回归、表示与正则化，逻辑回归 Linear regression, representation and regularization, logistic regression

时间安排与收获 Schedule and Outcome

• 在线科研学习+论文辅导学习Online research study + essay tutoring study

• 教授推荐信 Professor's'recommendation letter

• EI/CPCI/Scopus索引国际会议论文发表与收录（可用于申请）International conference papers indexed by EI/CPCI/Scopus (available for application)

• 结业证书 Certificate of completion

• 学习报告 Study report

项目优势 Program Advantages

1. 师资团队配置高

A.授课教授均为剑桥大学、牛津大学在职教授

B. 导师是牛津大学、剑桥大学博士生

C. 班主任负责项目全流程管理

D. 由位于剑桥的英国团队直接提供服务，中方团队配合

2. 小班教学体验

A.10-15人/班，师生比 1：5

B. 国际混合班

C. 可免费试听（*，依情况而定）

D. 学生体验好

3. 项目收获多、性价比高

A.教授亲笔签名的推荐信

B. 教授亲笔签名的结业证书

C. 导师签名的学习报告

D. CPCI、EI、国际会议等国际刊物论文全文发表（独立作者、*作者）

4. 推荐信含金量高

A.推荐信非模板化，有个体差异

B. 电子版推荐信1封

C. 3次网推（如需增加数量，可与教授协商）

D. EDU邮箱/非官方邮箱（可与教授协商）

E. 项目学生确保都有推荐信

5. 提供不*长的录播课程，学生可以任意观看

1. SENIOR TEAM STRUCTURE
A. All of the teaching staff are serving Cambridge or Oxford University professors. 
B. The course supervisor is a Cambridge and Oxford Phd Graduate. 
C. There is a separate Course Supervisor responsible for the wider programme management. 
D . Services in the UK are provided directly by the UK team, based in Cambridge, and supported by the Chinese team
2. Small class sizes
A. 10-15 students in a class, teacher ratio 1:5
B. International mixed classes
C.  Free taster session (limited, subject to availability)
D. Good study experience
3. Course and study outputs and outcome
A. A Letter of Recommendation signed by the Professor
B. A Certificate of Completion signed by the Professor
C. Study Report signed by Tutor
D. Full papers published in CPCI, EI, international conferences and other international journals
4. Multiple references
A. The Letter of Recommendation is personalised to the student. 
B. One electronic Recommendation Letter
C. Three on-line recommendation communications from the Professor (negotiable)
D. EDU email/unofficial email (negotiable with the Professor)
E. All students are guaranteed a Letter of Recommendation
5. Unlimited access to course recordings