国际学生入学条件
Must have a baccalaureate degree from a regionally accredited institution of higher education.Earned or will earn a four-year baccalaureate degree from a regionally acredited US institution, or an equivalent degree from a nationally recognized non-US institution.Earned a 3.00 GPA on a 4.00 scale or better in your baccalaureate study. If the applicant's native language is not English, proof of English competency with a minimum TOEFL score of 575 for the paper-based exam or 230 for the computer-based exam..While no specific undergraduate degree is required, a background in engineering, business, computer science, statistics, mathematics, or information technology is desirable, or alternatively strong work experience with data or analytics may be used. At a minimum at least one course each in calculus, statistics, and computer programming is required. Data Analytics Fundamentals may be required for students without a basic foundation in Data Analytics.
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雅思考试总分
6.0
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雅思考试指南
- 雅思总分:6
- 托福网考总分:60
- 托福笔试总分:575
- 其他语言考试:Pearson Academic Test of English: A minimum score of 59, all applicants
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申请截止日期: 请与IDP顾问联系以获取详细信息。
课程简介
数据分析工程硕士是由统计学系管理的Volgenau多学科学位课程,旨在让学生了解数据驱动决策所需的技术和方法。学生学习诸如数据挖掘,信息技术,统计建模,预测分析,优化,风险分析和数据可视化等主题。该课程面向希望成为金融,市场营销,运营,商业/政府情报和其他信息密集型小组的数据科学家和分析师的学生,这些小组会生成和使用大量数据。数据分析工程学硕士旨在为学生提供了解数据驱动决策所需的技术和方法。主题涵盖数据挖掘,信息技术,统计模型,预测分析,优化,风险分析和数据可视化。该课程针对希望成为金融,市场营销,运营,
The MS in Data Analytics Engineering is a Volgenau multidisciplinary degree program, administered by the Department of Statistics, and is designed to provide students with an understanding of the technologies and methodologies necessary for data-driven decision-making. Students study topics such as data mining, information technology, statistical modeling, predictive analytics, optimization, risk analysis, and data visualization. It is aimed at students who wish to become data scientists and analysts in finance, marketing, operations, business/government intelligence and other information intensive groups generating and consuming large amounts of data.The masters in data analytics engineering is designed to provide students with an understanding of the technologies and methodologies necessary for data-driven decision-making. Topics cover data mining, information technology, statistical models, predictive analytics, optimization, risk analysis, and data visualization. Aimed at students who wish to become data scientists and analysts in finance, marketing, operations, business intelligence, and other information-intensive groups generating and consuming large amounts of data, the program also has wider applications, including concentrations in digital forensics, financial engineering, and business analytics.
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