伦敦大学学院-计算机统计学和机器学习硕士

伦敦大学学院

Computational Statistics and

Machine Learning MSc

计算机统计学和机器学习硕士

课程领域：计算机科学

所属院系：工程科学

Computational Statistics and

Machine Learning MSc

计算机统计学和机器学习硕士

项目概述

This MSc teaches advanced analytical and computational skills for success in a data rich world. Designed to be both mathematically rigorous and relevant, the programme covers fundamental aspects of machine learning and statistics, with potential options in information retrieval, bioinformatics, quantitative finance, artificial intelligence and machine vision.

该项目提供高级分析和计算机技能，使学生能在这个充满数据的世界获得成功。项目的设计方面既有数学的严谨和相关信息，同时也覆盖了机器学习和统计学的基本方面，并提供关于信息搜索、生物信息学、量化金融、人工智能和机器视觉的选修课程。

课程结构

必修单元：

Supervised Learning (15 credits)

监督学习（15学分）

Statistical Modelling and Data Analysis (15 credits)

统计建模和数据分析（15学分）

选修单元：

Group One Options(15 credits)

第一组选修（15学分）

Graphical Models (15 credits)

图形模型（15学分）

Probabilistic and Unsupervised Learning (15 credits)

概率和无监督学习（15学分）

Group Two Options(30 to 60 credits)

第二组选修（30-60学分）

Advanced Deep Learning and Reinforcement Learning (15 credis)

高级深度学习和加强学习（15学分）

Advanced Topics in Machine Learning (15 credits)

机器学习中的高级主题（15学分）

Applied Machine Learning (15 credits)

应用机器学习（15学分）

Approximate Inference and Learning in Probabilistic Models (15 credits)

概率模型的近似推理和学习（15学分）

Information Retrieval and Data Mining (15 credits)

信息搜索和数据挖掘（15学分）

Introduction to Deep Learning (15 credits)

深度学习概述（15学分）

Machine Vision (15 credits)

机器视觉（15学分）

Statistical Natural Language Processing (15 credits)

统计自然语言处理（15学分）

Group Three Options(15 credits)

第三组选修（15学分）

Applied Bayesian Methods (15 credits)

应用贝叶斯方法（15学分）

Statistical Design of Investigations (15 credits)

调研的统计学设计（15学分）

Statistical Inference (15 credits)

统计学推理（15学分）

项目申请要求

GPA:

Bachelor's degree with a minimum overall average mark of85%.

本科学士学位综合均分不低于85%。

语言成绩要求：良好

IELTS：综合得分7.0，单项不低于6.5

TOFEL：综合得分100，阅读24 写作30 口语20 听力30

其他要求：

in a highly quantitative subject such as computer science, statistics, mathematics, electrical engineering or the physical sciences.

专业要求：高度量化专业如，计算机科学、统计学、数学、电子工程或者物理科学

Relevant work experience may also be taken into account. Students must be comfortable with undergraduate-level mathematics; in particular it is essential that the candidate will have knowledge of statistics at an intermediate undergraduate level. The candidate should also be proficient in linear algebra and multivariable calculus.

相关的工作经历将纳入考虑。学生应该具备良好的本科数学水平，尤其很重要的是，候选者必须有统计学的本科中等水平。候选人必须流畅掌握线性代数和变量计算。

学费和申请日期

2018/19学年学费

海外学生：26,670英镑

2018/19学年申请日期：

开放申请：16 October 2017

结束申请：15 June 2018

就业方向

There is a strong national and international demand for graduates with skills at the interface of traditional statistics and machine learning. Substantial sectors of UK industry, including leading, large companies already make extensive use of computational statistics and machine learning techniques in the course of their business activities. Globally there are a large number of very successful users of this technology, many located in the UK. Areas in which expertise in statistics and machine learning is in particular demand include: finance, banking, insurance, retail, e-commerce, pharmaceuticals, and computer security. Graduates have gone on to further study at, for example, the Universities of Cambridge, Helsinki, Chicago, as well as at UCL. The MSc is also ideal preparation for a PhD, in statistics, machine learning or a related area.

具备传统统计学和机器学习的交叉技能的毕业生广受国内和国际欢迎。英国的各个重要行业，包括领头的大规模公司已经开始在他们的商业操作中大规模使用计算机统计学和机器学习技能。在全球，有一大部分使用这种技术的成功者，很多都在英国。非常需要统计学和机器学习交叉技能的部门包括：金融、银行、保险、零售、电子商务、医药和计算机安全。毕业生也可能选择进一步的学习，例如，剑桥、赫尔辛基、芝加哥以及UCL。该项目同样也是数据学、机器学习等相关领域博士学习的很好准备。

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