东北大学

Northeastern University

学校官网
区域分类:Urban 学校类型:私立混合
学生数量:30013 研究生数量:13711 国际生数量:5938 (占比31.60%

东北大学(简称NEU)是美国顶尖私立研究型大学,也是全美规模最大的私立大学,位于美国东北部马萨诸塞州波士顿市的芬威文化区,拥有73亩的校园,是一片坐落在波士顿中心地带的绿洲,距离芬威公园、购物中心、咖啡厅、交响乐厅和艺术博物馆都只有几分钟的路程。东北大学工程、临床医学、生物医学、药剂学、国际商务等专业均位列全美前50,其本科由八大学院70个专业组成,研究生由九大学院组成,除此之外还在夏洛特以及西雅图开设了两个授课校区,热门专业为工程、商科、物理治疗、药剂学、计算机科学、护理学、新闻学、市场学和电机工程等。特别的是,东北大学的就业服务位列全美第1,理工科毕业生在美国东北部公司的受欢迎程度仅次于麻省理工学院与哈佛大学。

知名校友

兹·斯通,杰夫·克拉克,肖恩·范宁

热门专业

Business, Management, Marketing, and Related Support Services, Engineering, Computer and Information Sciences and Support Services, Biological and Biomedical Sciences, Health Professions and Related Programs, Social Sciences, Communication, Journalism, and Related Programs, Visual and Performing Arts, Psychology, Mathematics and Statistics

提供学位

Bachelor's, Master's, Post-master's certificate, Doctorate - professional practice, Doctorate - research/scholarship

本科申请信息

基本信息

本科录取率
7%
本科生数量
15891
学费估算
$66,162
TOEFL Code
3665
学期制度
semester

入学成绩

SAT录取均分
1495
ACT录取均分
34
GPA录取均分
4
SAT要求
Neither SAT nor ACT
TOEFL要求
最低:92,网考成绩:Required of some
IELTS要求
Required of some
面试要求
Neither required/recommended
Common App 要求
Yes

转学相关

转学所需最低学分
12
转学最低GPA
N/A
转学接受学期
Fall, Spring
转学生比例
5.00%
转学录取率
30.00%

申请截止日期

  • 秋季
  • 常规
    Jan. 1
  • 提早
    Nov. 1
  • 转学生
    4.1
  • 春季
  • 转学生
    10.1
国际生
Fall:Jan. 1
SAT/ACT提交
Jan. 1

学院及研究生项目

理学院

NEU College of Science

学院项目

Master of Science in Environmental Science & Policy

基本信息

学分
暂无
项目时长
暂无
学费估算
暂无
GMAT Code
暂无
托福/GRE Code
3682

申请截止日期

  • 秋季
  • 早申请
    6月1日
  • 春季
  • 常规
    10月1日

申请信息

项目官网 查看该项目详情
Master of Science in Mechanical Engineering
Master of Science program in Mathematics
MS in Applied Mathematics
Master of Science in Bioinformatics

艺术及传媒及设计学院

NEU College of Arts Media Design

学院项目

MS in Architecture

基本信息

学分
32
项目时长
1
学费估算
$1500/credit
GMAT Code
暂无
托福/GRE Code
3682

申请截止日期

  • 秋季
  • 常规
    2月1日

申请信息

GPA
2.7
TOEFL
92.0
Prerequisite
GRETOEFL/IELTS
项目官网 查看该项目详情
Master's of Science in Game Science and Design
Master of Arts in Journalism

专业研究学院

NEU College of Professinal Study

学院项目

Master of Science in Human Resources Management

基本信息

学分
暂无
项目时长
暂无
学费估算
暂无
GMAT Code
暂无
托福/GRE Code
暂无

申请截止日期

  • 秋季

申请信息

项目官网 查看该项目详情
MS in Global Studies and International Relations
MS in Commerce and Economic Development
MS in Nonprofit Management
Master of Professional Studies in Informatics
MS in Corporate and Organizational Communication
Master in Regulatory Affairs for Drugs, Biologics, and Medical Devices
MPS in Analytics
Master of Professional Studies in Digital Media Connect
MS in Project Management
Digital Media MA

社科及人文学院

NEU College of Social Sciences and Humanities

学院项目

Master of Arts in Economics/Ph.D. Program in Applied Economics

基本信息

学分
32
项目时长
2
学费估算
$1,600/credit
GMAT Code
暂无
托福/GRE Code
3682

申请截止日期

  • 秋季
  • 常规
    6月15日(International)
  • 早申请
    12月15日(Ph.D. Program)

申请信息

TOEFL
85.0
IELTS
6.5
项目官网 查看该项目详情
Master of Public Policy
Master of Public Administration

商学院

NEU DAmoreMcKim School of Business

学院信息

  • 录取率
    35.3%
  • 就业率
    42.20%
  • 平均起薪
    87,773

录取平均成绩

  • GRE
    V 156.00 /Q 158.0 /A 3.70
  • GMAT
    633.0
  • 平均本科GPA
    3.34

语言要求

  • 托福
    最低100.00 平均102.00
  • 雅思
    最低7.00

学院项目

Master's in International Management

基本信息

学分
暂无
项目时长
暂无
学费估算
暂无
GMAT Code
暂无
托福/GRE Code
暂无

申请截止日期

  • 秋季
  • 常规
    11月5日
  • Round1
    1月20日
  • Round2
    3月15日

申请信息

项目官网 查看该项目详情
Marketing
MS in International Business
MS in Finance
MS in Business Analytics
MS in Accounting

计算机与信息科学学院

NEU Collge of Computer and Information Science

学院项目

MS in Data Science

基本信息

学分
32
项目时长
2
学费估算
$24,489
GMAT Code
暂无
托福/GRE Code
3665

申请截止日期

  • 秋季
  • 早申请
    5月1日
  • 春季
  • 常规
    10月15日

申请信息

GPA
3.0
TOEFL
100.0
GRE
V 150.0 / Q 155.0 / A 4.0
Prerequisite
Placement Exams Each incoming masters student, regardless of his or her background, takes two placement exams administered one week prior to the beginning of the semester. The two exams cover fundamentals of computer science and programming skills and basic statistics, probability, and linear algebra. If the student does not get a B or above in a part of the placement exam, then the student must take the corresponding introductory course. Introduction to Programming for Data Science (DS 5010) The introductory course on fundamentals of programming and data structures covers data structures (lists, arrays, trees, hash tables, etc.), program design, programming practices, testing, debugging, maintainability, data collection techniques, and data cleaning and preprocessing. This course will have a class project where the students will use the concepts they learn to collect data from the web, clean, and preprocess and ready for analysis. Introduction to Linear Algebra and Probability for Data Science (DS 5020) The introductory course on basics of statistics, probability, and linear algebra covers random variables, frequency distributions, measures of central tendency, measures of dispersion, moments of a distribution, discrete and continuous probability distributions, chain rule, Bayes' rule, correlation theory, basic sampling, matrix operations, trace of a matrix, norms, linear independence and ranks, inverse of a matrix, orthogonal matrices, range and null space of a matrix, the determinant of a matrix, positive semidefinite matrices, eigenvalues and eigenvectors.
项目简介
The Master of Science in Data Science curriculum requires five core courses that jointly represent the essential technical skills in data science. Two courses in algorithms and data processing examine foundational concepts and languages, focusing on data representation, storage, manipulation, and query, as well as large-scale computing and optimization. Two core courses in machine learning and data mining introduce concepts on data modeling, representation, uncovering associations, and making predictions. The capstone course presents a holistic view of data science. Through experiential learning, students are exposed to the real-world challenges of implementing data science techniques to solve meaningful problems and effectively communicate with data. The courses are tailored toward technically or mathematically trained students. The five core courses include: Two core courses in algorithms and data processing Two core courses in machine learning and data mining One core course in information visualization Three elective courses are drawn from a selection of courses across Northeastern. Learning Outcomes Students who complete the MS degree will be able to: Collect data from numerous sources (databases, files, XML, JSON, CSV, and Web APIs) and integrate them into a form in which the data is fit for analysis Use R and Python to explore data, produce summary statistics, perform statistical analyses; use standard data mining and machine-learning models for effective analysis Select, plan, and implement storage, search, and retrieval components of large-scale structure and unstructured repositories Retrieve data for analysis, which requires knowledge of standard retrieval mechanisms such as SQL and XPath, but also retrieval of unstructured information such as text, image, and a variety of alternate formats Match the methodological principles and limitations of machine learning and data mining methods to specific applied problems and communicate the applicability and the advantages/disadvantages of the methods in the specific problem to nondata experts Carry out the full data analysis workflow, including unsupervised class discovery, supervised class comparison, and supervised class prediction; Summarize, interpret, and communicate the analysis of results Organize visualization of data for analysis, understanding, and communication; choose appropriate visualization method for a given data type using effective design and human perception principle Develop methods for modeling, analyzing, and reasoning about data arising in one or more application domains such as social science, health informatics, web and social media, climate informatics, urban informatics, geographical information systems, business analytics, bioinformatics, complex networks, public health, and game design Manage, process, analyze, and visualize data at scale. This outcome allows students to handle data where the conventional information technology fail.
项目官网 查看该项目详情
Master of Science in Computer Systems Engineering
MS in Computer Science

建筑学院

NEU School of Architecture

学院项目

Master of Design For Sustainable Urban Environments

基本信息

学分
64
项目时长
2
学费估算
$1,569 (per credit hour)
GMAT Code
暂无
托福/GRE Code
3682

申请截止日期

  • 秋季
  • 常规
    5月1日
  • 早申请
    2月1日
  • 春季
  • 常规
    10月1日

申请信息

GPA
3.0
TOEFL
100.0
IELTS
7.0
项目官网 查看该项目详情
Master of Design For Sustainable Urban Environments

工程学院

NEU College of Engineering

学院信息

  • 录取率
    42.2%

录取平均成绩

  • GRE
    V 149.00 /Q 162.0 /A 3.00
  • 平均本科GPA
    3.26

语言要求

  • 托福
    最低79.00 平均97.00
  • 雅思
    最低6.00

学院项目

Master of Science in Robotics

基本信息

学分
暂无
项目时长
暂无
学费估算
暂无
GMAT Code
暂无
托福/GRE Code
3665

申请截止日期

  • 秋季
  • 常规
    6月1日(outside the USA);7月1日(inside the USA)
  • 早申请
    1月15日

申请信息

项目官网 查看该项目详情
MS in Information Systems
MS in Data Analytics Engineering
MS in Electrical and Computer Engineering
MS in Physics
Master of Science in Civil Engineering
MS in ECE
Master of Science in Mechanical Engineerin
MS in Environmental Engineering
Master of Science in Bioengineering
MS in Industrial Engineering
Master of Science in Information Systems

医学院

NEU Bouv College of Health Sciences

学院项目

Applied Psychology

基本信息

学分
暂无
项目时长
暂无
学费估算
暂无
GMAT Code
暂无
托福/GRE Code
暂无

申请截止日期

  • 秋季
  • 常规
    6.1
  • 早申请
    1.15

申请信息

项目官网 查看该项目详情
Master of Public Health
MS in Applied Behavior Analysis

法学院

NEU School of Law

学院项目

Master of Laws (LLM)

基本信息

学分
33
项目时长
1月2日
学费估算
$50,700
GMAT Code
暂无
托福/GRE Code
8395(LSAC)/3658(T)

申请截止日期

  • 秋季
  • 早申请
    2月1日

申请信息

Prerequisite
LSAT TOEFL/IELTS
项目官网 查看该项目详情