Master of Science in Computer Science and Engineering - Data and Software Systems-内华达大学雷诺分校申请条件

Master of Science in Computer Science and Engineering - Data and Software Systems

内华达大学雷诺分校

University of Nevada Reno

美国

学历文凭
Masters Degree
专业院系
Department of Computer Science and Engineering
开学时间
课程时长
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国际学生入学条件

Applicants to the master’s degree program should have a bachelor’s degree in engineering, mathematics, or science and have minimum experience that includes the equivalent of a Computer Science and Engineering minor. Applicants should further meet the following minimum criteria and the materials for admission: A minimum undergraduate GPA of 3.0. A minimum GRE Quantitative score of at least 156. International applicants have an additional language requirement as outlined on the Graduate School’s international admission page. A one-page personal statement describing research interests and career goals. Two letters of recommendation. TOEFL: 550 (paper) or 79 (internet) IELTS: 6.5 (academic version)

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IDP—雅思考试联合主办方
雅思考试总分
6.5
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雅思考试指南

雅思总分：6.5
托福网考总分：79
托福笔试总分：550
其他语言考试：Pearson (PTE): 59, Cambridge: 176, Duolingo: 105

CRICOS代码：
申请截止日期：请与IDP顾问联系以获取详细信息。

课程简介

Researchers in data and software systems are developing computational and software solutions to advance the collection and use of big data for scientific research. Research in this area also focuses on enhancing human-computer interaction and facilitating data and software-intensive interdisciplinary projects.<br>Faculty specializing in software systems are leveraging the power of modern computing and technology to develop new techniques and tools that increase productivity in research projects and industrial applications. Research in human-computer interaction focuses on developing new locomotion techniques for navigation in virtual reality and new ways of interacting, such as brain-computer interfaces.<br><br>In big data, we aim to advance fundamental data-centric research and data-driven domain discoveries, build data infrastructure for scientific research, and develop a 21st-century data-skilled workforce, which is in very high demand.

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