国际学生入学条件
The MS in Data Science is designed for individuals with career backgrounds or undergraduate degrees in business, engineering, computer science, physical/life/social sciences, mathematics, the liberal arts, and education who want to enhance their data analytics and information science skills and credentials.
Statement of purpose: 300 - 600 words. Indicate your graduate study objectives, research interests and experience, and business or industry experience if applicable. If you are applying for a teaching or research assistantship, include any special skills or experience that would assist in assistantship decisions.
Official transcripts: from all post-secondary institutions attended (regardless if a credential is earned or not). Transcripts should show class rank if available. Minimum requirements for admission are a 3.0 GPA (out of 4.0), although other evidence of professional competence can be considered for students who do not meet this criteria
Official GRE score: sent directly from ETS, copies/scans not accepted. Required except by those who are or are about to be graduates of the UMassD College of Engineering.
3 letters of recommendation: from persons in the field of your academic major at the institution most recently attended or from supervisors familiar with your recent job performance. BS/MS applicants are encouraged to include a recommendation from a department faculty member willing to advise their graduate research.
Resume.
IELTS: 6.5
TOEFL PBT: 550
TOEFL IBT: 80
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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:80
- 托福笔试总分:550
- 其他语言考试:Official GRE score
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
The master's degree program in data science prepares you for leadership positions in data analytics, information management, and knowledge engineering. It is jointly offered by the departments of Computer Science in Engineering and Mathematics in Arts & Sciences. With a master's degree in data science, you will: develop skills in computer programming, statistics, data mining, machine learning, data analysis, and visualization be prepared to solve challenging problems involving large, diverse data sets from different application domains You will explore the rapidly emerging fields of data analytics and discovery informatics-which integrates mathematics and computer science for the quantification and manipulation of information from a cognate area of application (such as science, engineering, business, sociology, healthcare, planning).
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