近些年，隨著數(shù)據(jù)運營所帶來得利好日益明顯，很多機(jī)構(gòu)或者企業(yè)開始重視海量數(shù)據(jù)背后所蘊藏的無限“財富”，從而對數(shù)據(jù)科學(xué)人才的需求量與日俱增，國內(nèi)目前鮮少有大學(xué)開設(shè)此專業(yè)，而美國很多大學(xué)都開設(shè)了數(shù)據(jù)科學(xué)專業(yè)，其中最出色的就是約翰霍普金斯大學(xué)，下面，小編就帶大家深入了解約翰霍普金斯大學(xué)的數(shù)據(jù)科學(xué)碩士專業(yè)，希望對大家有所幫助：

　　Data Science, Master of Science

　　數(shù)據(jù)科學(xué)項目平衡理論和應(yīng)用，使你可以促進(jìn)你的職業(yè)生涯長期。

　　嚴(yán)格的課程集中于計算機(jī)科學(xué)、統(tǒng)計學(xué)和應(yīng)用數(shù)學(xué)的基礎(chǔ)，同時結(jié)合了現(xiàn)實世界的例子。通過向?qū)嵙?xí)工程師和數(shù)據(jù)科學(xué)家學(xué)習(xí)，畢業(yè)生可以勝任從數(shù)據(jù)管道、存儲到統(tǒng)計分析以及引出數(shù)據(jù)故事等各種專業(yè)工作。

　　課程設(shè)置：

　　Prerequisite Courses 1

　　EN.605.101 Introduction to Python

　　EN.605.201 Intro to Programming Using Java

　　EN.605.202 Data Structures

　　EN.605.203 Discrete Mathematics

　　EN.605.206 Introduction to Programming Using Python

　　EN.625.201 General Applied Mathematics

　　EN.625.250 Multivariable Calculus and Complex Analysis

　　EN.625.251 Introduction to Ordinary and Partial Differential Equations

　　EN.625.252 Linear Algebra

　　Foundation Courses

　　EN.685.621 Algorithms for Data Science 2

　　EN.625.603 Statistical Methods and Data Analysis 2

　　Required Courses

　　EN.685.648 Data Science

　　EN.605.662 Data Visualization

　　EN.625.661 Statistical Models and Regression

　　EN.605.641 Principles of Database Systems

　　or EN.605.649 Introduction to Machine Learning

　　EN.625.615 Introduction to Optimization 3

　　or EN.625.664 Computational Statistics

　　Select one EN.625.xxx course from Electives or Additional Selections

　　Electives

　　Select one of the following:

　　EN.605.741 Large-Scale Database Systems

　　EN.605.746 Advanced Machine Learning

　　EN.605.748 Semantic Natural Language Processing

　　EN.605.788 Big Data Processing Using Hadoop

　　Select one of the following:

　　EN.625.714 Introductory Stochastic Differential Equations with Applications

　　EN.625.721 Probability and Stochastic Process I

　　EN.625.722 Probability and Stochastic Process II

　　EN.625.725 Theory Of Statistics I

　　EN.625.726 Theory of Statistics II

　　EN.625.734 Queuing Theory with Applications to Computer Science

　　EN.625.740 Data Mining

　　EN.625.741 Game Theory

　　EN.625.743 Stochastic Optimization & Control

　　EN.625.744 Modeling, Simulation, and Monte Carlo

　　Additional Selections

　　EN.605.625 Probabilistic Graphical Models

　　EN.605.628 Applied Topology

　　EN.605.632 Graph Analytics

　　EN.605.633 Social Media Analytics

　　EN.605.635 Cloud Computing

　　EN.605.645 Artificial Intelligence

　　EN.605.647 Neural Networks

　　EN.605.649 Introduction to Machine Learning

　　EN.605.724 Applied Game Theory

　　EN.605.725 Queuing Theory with Applications to Computer Science

　　EN.605.726 Game Theory

　　EN.625.601 Real Analysis

　　EN.625.609 Matrix Theory

　　EN.625.611 Computational Methods

　　EN.625.618 Discrete Hybrid Optimization

　　EN.625.620 Mathematical Methods for Signal Processing

　　EN.625.623 Introduction to Operations Research: Probabilistic Models

　　EN.625.633 Monte Carlo Methods

　　EN.625.636 Graph Theory

　　EN.625.638 Neural Networks

　　EN.625.641 Mathematics of Finance

　　EN.625.642 Mathematics of Risk, Options, and Financial Derivatives

　　EN.625.662 Design and Analysis of Experiments

　　EN.625.663 Multivariate Statistics and Stochastic Analysis

　　EN.625.665 Bayesian Statistics

　　EN.625.680 Cryptography

　　EN.625.687 Applied Topology

　　EN.625.690 Computational Complexity and Approximation

　　EN.625.692 Probabilistic Graphical Models

　　EN.625.695 Time Series Analysis

　　EN.625.717 Advanced Differential Equations: Partial Differential Equations

　　EN.625.718 Advanced Differential Equations: Nonlinear Differential Equations and Dynamical Systems

　　EN.625.728 Theory of Probability

　　Independent Study

　　EN.685.795 Capstone Project in Data Science

　　EN.685.801 Independent Study in Data Science I

　　EN.685.802 Independent Study in Data Science II

　　入學(xué)要求：

　　三個學(xué)期或四分之五的微積分課程，包括多元微積分;

　　一學(xué)期/學(xué)期的高等數(shù)學(xué)(離散數(shù)學(xué)優(yōu)先，線性代數(shù)和微分方程也可以);

　　一學(xué)期/學(xué)期的Java或Python (c++也可以，但學(xué)生必須至少對Java或Python有一定的了解);

　　一學(xué)期/學(xué)期數(shù)據(jù)結(jié)構(gòu)

　　線性代數(shù)或微分方程將被接受代替離散數(shù)學(xué)。必須在每門預(yù)備課程中取得B -或更高的成績。申請人之前的教育不包括上述所列的先決條件，仍然可以在臨時狀態(tài)下注冊，然后一旦他們完成了缺失的先決條件，完全錄取狀態(tài)。缺少先決條件可能與約翰霍普金斯工程(所有先決條件可用)或在另一個地區(qū)認(rèn)可的機(jī)構(gòu)完成。申請人在本科后半部分的學(xué)習(xí)中，平均成績至少為3.0(滿分為4.0)(B級或以上)。如果他們希望他們的學(xué)術(shù)和專業(yè)背景被考慮，申請人可以提交詳細(xì)的résumé。

　　除了微積分的要求外，還提供了計算機(jī)科學(xué)和數(shù)學(xué)的本科課程。

　　綜上所述，以上講的就是關(guān)于約翰霍普金斯大學(xué)數(shù)據(jù)科學(xué)碩士專業(yè)的相關(guān)問題介紹，希望能給各位赴美留學(xué)的學(xué)子們指點迷津。近年來，赴美留學(xué)一直是廣大學(xué)生最熱門的話題，同時，很多學(xué)生對于簽證的辦理、院校的選擇、就業(yè)的前景、學(xué)習(xí)的費用等諸多問題困擾不斷，別擔(dān)心，IDP留學(xué)專家可以為你排憂解難，同時，更多關(guān)于赴美留學(xué)的相關(guān)資訊在等著你，絕對讓你“瀏覽”忘返。在此，衷心祝愿各位學(xué)子們能夠順利奔赴自己心目中理想的學(xué)校并且學(xué)業(yè)有成!