国际学生入学条件
A master's degree is not necessarily a requirement for this program, relevant research experience may be considered in lieu of a master's degree. Students who are completing their Bachelor's degree however, are not yet prepared to apply. Entering students should have a foundation in microeconomics, epidemiology, and statistics. Most applicants, however, do hold a master's degree and have had relevant work experience. Students without prior master's-level coursework in these areas will need to remedy deficiencies in their first year. Experience working in the health sector is viewed favorably by the Admissions Committee as is prior research experience. A criterion for admission is at least a B (3.0) grade-point average or the equivalent in work completed after the first two years of a bachelor's degree program and in all post-baccalaureate course work. Applicants must submit Graduate Records Exam (GRE) general scores not more than five years old. The average entering student has a verbal score above the 90th percentile and a quantitative scores about the 75th percentile. A minimum of three letters of recommendation must be submitted as part of the application process, two sets of original transcripts are also required. Writing samples in the form of published articles and journal abstracts may be submitted. A grade point average of B or better (3.0), If the applicant comes from a country or political entity (e.g., Quebec) where English is not the official language, adequate proficiency in English to do graduate work, as evidenced by a TOEFL score of at least 90 on the iBT test, 570 on the paper-and-pencil test, or an IELTS Band score of at least 7 on a 9-point scale (note that individual programs may set higher levels for any of these)
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IDP—雅思考试联合主办方

雅思考试总分
7.0
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雅思考试指南
- 雅思总分:7
- 托福网考总分:90
- 托福笔试总分:570
- 其他语言考试:NA
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 Population & Data Science specialty field trains students for research careers applying cutting-edge quantitative methods to pressing policy questions in health services research and population health. Students will learn and integrate methods from key disciplinary strengths at Berkeley: biostatistics, social science approaches such as econometrics and demography, and the rapidly evolving set of big data data science innovations advanced in UC Berkeley's Division of Computing Data Science, and Society. The explosion of health sector data availability, along with Berkeley's innovation hub positioning, make this an excellent track for students looking to become quantitative experts who can lead research across a wide variety of population health policy questions.
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