国际学生入学条件
International applicants should have college preparatory coursework in the core subjects of English (if offered), mathematics, physical science, and social science reflected throughout their high school academic careers. Students applying to the School of Engineering must have taken secondary school level physics and chemistry.
International applicants who have completed one year or more of full-time coursework at a post-secondary institution in the United States. The total amount of academic work completed must be officially graded by the registrar of that institution and have a cumulative GPA value of 3.0 or higher, excluding ESL curriculum.
International applicants who have received a degree from an international post-secondary institution whose language of instruction is English. Official documentation will be required from the institution's Registrar's office stating that the medium of instruction for the degree received was English.
International applicants who have achieved 510 or higher on the Evidence-Based Reading and Writing section of the SAT or 24 or higher on the English, Reading, and Composite on the ACT.
International English Language Testing System (IELTS), or Duolingo are required for International applicants whose primary language is not English. The minimum score requirement for the TOEFL is 550 (paper-based), 213 (computer-based), or 79 (internet-based), minimum score requirement for the IELTS exam is 6.5, minimum Duolingo score requirement is 100. Test scores must be sent directly to the University of Connecticut from the respective test provider.
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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:Duolingo score requirement is 100
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
Data are a new economic asset of the 21st century that touches all aspects of the society. Business Data Analytics Program provides a business degree with a special emphasis in the application of data analytics to business problems. Students will acquire a set of practical data analytics skills including understanding patterns in data, applying analytical frameworks, constructing predictive models, analyzing social networks and discovering hidden relationships in data. Students will learn how to present data using modern visualization techniques, and will get acquainted with the state of the art data analytics software.
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