约翰霍普金斯大学-数据科学专业

数据科学硕士

master of science in ata science

课程介绍

the rigorous curriculum focuses on the funamentals of computer science, statistics, an applie mathematics, while incorporating real-worl examples. with options to stuy online an on-site in state-of-the-art facilities at the johns hopkins applie physics laboratory, stuents learn from practicing engineers an ata scientists. grauates are prepare to succee in specialize jobs involving everything from the ata pipeline an storage, to statistical analysis an eliciting the story the ata tells.

严格的课程侧重于计算机科学，统计学和应用数学的基础知识，同时结合了真实的示例。在约翰霍普金斯大学应用物理实验室，您可以选择在线学习和在最先进的设备中进行现场学习，向在职工程师和数据科学家学习。毕业生准备成功完成涉及数据管道和数据存储，统计分析和得出数据故事的专业工作。

upon completing the egree program, stuents will:

完成课程学习后，学生将能够：

1. effectively an competitively respon to the growing eman for ata scientists.

有效且有竞争力地应对数据科学家日益增长的需求。

1. balance both the theory an practice of applie mathematics an computer science to analyze an hanle large-scale ata sets.

平衡应用数学和计算机科学的理论和实践，以分析和处理大规模数据集。

1. escribe an transform information to iscover relationships an insights into complex ata sets.

描述和转换信息，以发现与复杂数据集之间的关系和见解。

1. create moels using formal techniques an methoologies of abstraction that can be automate to solve real-worl problems.

使用形式化技术和抽象方法创建模型，这些模型和方法可以自动解决实际问题。

入学要求

you must meet the general amission requirements that pertain to all master＇s egree caniates.

您必须符合所有硕士学位候选人的一般入学要求。

your prior eucation must inclue the following prerequisites: ﹙1﹚ three semesters or five quarters of calculus, which inclues multivariate calculus; ﹙2﹚ one semester/term of avance math ﹙iscrete mathematics is strongly preferre but linear algebra an ifferential equations will be accepte﹚; ﹙3﹚ one semester/term of java or python ﹙c++ will be accepte but the stuent must be at least also somewhat knowlegeable in java or python﹚; an ﹙4﹚ one semester/term of ata structures. linear algebra or ifferential equations will be accepte in lieu of iscrete mathematics. a grae of b or better must have been earne in each of the prerequisite courses.

您的本科教育必须包括以下先决条件：（1）上过三个学期或五个季度的微积分，其中包括多元微积分；（2）一学期的高数（最好是离散数学，但可以接受线性代数和微分方程式）；（3）一个学期的java或python（可以接受c ++，但学生必须至少还具有一定的java或python知识）；（4）一学期的数据结构。可以使用线性代数或微分方程代替离散数学。每个先决课程必须达到b-或更好的成绩。

if your prior eucation oes not inclue the prerequisites liste above, you may still be amitte uner provisional status, followe by full amission once you have complete the missing prerequisites. missing prerequisites may be complete with johns hopkins engineering or at another regionally accreite institution.

如果您的本科教育不包括上面列出的先决条件，则您仍然可以临时身份被录取，一旦您完成缺少的前提条件，便可以被完全录取。缺少先决条件的人员可能会与johns hopkins engineering或其他地区认可的机构共同完成。

语言要求

a minimum score of 600 ﹙paper-base﹚, 250 ﹙computer-base﹚, or 104 ﹙web-base﹚ is require on the toefl. for the ielts, an overall ban score of at least 7.0 is require. the amissions office requires official copies of all results.

toefl的最低分数要求为600（笔试），250（机考）或104（网络考试）。对于雅思考试，总分至少需要7.0。招生办公室需要所有成绩的正式副本。

课程安排

prerequisite courses 先决课程

introuction to python python简介

intro to programming using java java编程简介

ata structures 数据结构

iscrete mathematics 离散数学

general applie mathematics 通用应用数学

multivariable calculus an complex analysis 多变量微积分和复杂分析

introuction to orinary an partial ifferential equations 常微分方程和偏微分方程介绍

linear algebra 线性代数

applicants whose prior eucation oes not inclue the prerequisites liste uner amission requirements may still be amitte uner provisional status, followe by full amission once they have complete the missing prerequisites. all prerequisite courses are available at johns hopkins engineering. these courses o not count towar the egree or certificate requirements.

先前的教育未包括入学要求中列出的先决条件的申请人仍可以临时身份被录取，一旦完成缺少的先决条件，则可以被完全录取。所有先修课程都可以在johns hopkins engineering获得。这些课程不计入学位或证书要求。

founation courses

基础课程

statistical methos an ata analysis 统计方法与数据分析

algorithms for ata science 数据科学算法

these require founation courses must be taken or waive before all other courses in their respective programs.

这些必修的基础课程必须在其各自课程的所有其他课程之前接受或放弃。

require courses 必修课程

principles of atabase systems or introuction to machine learning 数据库系统原理或机器学习导论

ata visualization 数据可视化

introuction to optimization * or computational statistics 优化或计算统计简介

statistical moels an regression 统计模型和回归

ata science 数据科学

electives 选修课

select one 以下课程选一

large-scale atabase systems 大型数据库系统

avance machine learning 高级机器学习

semantic natural language processing 语义自然语言处理

big ata processing using haoop 使用haoop进行大数据处理

select one 以下课程选一

introuctory stochastic ifferential equations with applications 随机差分微分方程及其应用

probability an stochastic process i 概率与随机过程i

probability an stochastic process ii 概率与随机过程ii

theory of statistics i 统计理论i

theory of statistics ii 统计理论ii

queuing theory with applications to computer science 排队论及其在计算机科学中的应用

ata mining 数据挖掘

game theory 博弈论

stochastic optimization & control 随机优化与控制

moeling, simulation, an monte carlo 建模，仿真和蒙特卡洛

aitional selections 额外选修课

probabilistic graphical moels 概率图形模型

applie topology 应用拓扑

graph analytics 图形分析

social meia analytics 社交媒体分析

clou computing 云计算

artificial intelligence 人工智能

neural networks 神经网络

introuction to machine learning 机器学习简介

applie game theory 应用博弈论

queuing theory with applications to computer science 排队论及其在计算机科学中的应用

game theory 博弈论

real analysis 真实分析

matrix theory 矩阵论

computational methos 计算方法

iscrete hybri optimization 离散混合优化

mathematical methos for signal processing 信号处理的数学方法

introuction to operations research: probabilistic moels 运筹学概论：概率模型

monte carlo methos 蒙特卡洛方法

graph theory 图形论

neural networks 神经网络

mathematics of finance 金融数学

mathematics of risk, options, an financial erivatives 风险，期权和金融衍生工具数学

esign an analysis of experiments 实验设计和分析

multivariate statistics an stochastic analysis 多元统计与随机分析

bayesian statistics 贝叶斯统计

cryptography 密码学

applie topology 应用拓扑

computational complexity an approximation 计算复杂度和近似值

probabilistic graphical moels 概率图形模型

time series analysis 时间序列分析

avance ifferential equations: partial ifferential equations 高级微分方程：偏微分方程

avance ifferential equations: nonlinear ifferential equations an ynamical systems 高级微分方程：非线性微分方程和动力学系统

theory of probability 概率论

inepenent stuy 自主学习

capstone project in ata science 数据科学实案项目

inepenent stuy in ata science i 数据科学i自主学习

inepenent stuy in ata science ii 数据科学ii自主学习

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