国际学生入学条件
Entry into the Master of Information (MI) program is competitive. Admission is based on a number of factors including prior academic performance at an accredited academic institution, test scores, professional work experience, standardized English proficiency test scores (for International students only), at least two letters of recommendation and a personal statement. Overall cumulative grade point average of 3.0 is typically the minimum requirement though applicants with lower GPAs are encouraged to apply and should discuss their GPA and undergraduate learning experiences in the Personal Statement. TOEFL – Test Of English as a Foreign Language - The minimum required score for admission is 94+ for the IBT test or 587 for the PBT test. Please note scores must be recent, within the past three years. IELTS – International English Language Testing System - The minimum required score for admission is 6.5+. Please note scores must be recent, within the past three years. Two letters are required. Letters of recommendation should focus on academic capacity (e.g., problem solving, thinking, analytical, and reflective skills) to undertake a rigorous program of graduate study, rather than on workplace efficiency and character traits. A Personal Statement is required as part of the admissions process. In approximately 750 words, state interests and career aspirations in pursuing the Master of Information degree. Rutgers School of Communication and Information will grant a GRE waiver to applicants meeting one or more of these requirements: A GPA above 3.0 on a 4.0 scale (from a U.S. institution) A completed advanced or master’s degree, Applicants may submit GMAT, MCAT and LSAT scores in place of GRE scores.
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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:94
- 托福笔试总分:587
- 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
这种专注力将教育学生识别数据驱动的问题,并使用包括数据/信息检索,存储,分析和可视化在内的分析方法解决问题。这些技能可以应用于越来越依赖于数据可用性和使用的领域中的各种专业职责和机会,这些领域包括金融,电子商务,医疗保健,竞争情报和国防。
This concentration will educate students about identifying data-driven problems, and solving them using analytics approaches that include data/information retrieval, storage, analysis, and visualization. These skills can be applicable to a wide rage of professional responsibilities and opportunities available in the areas that increasingly rely on availability and use of data, including finance, e-commerce, healthcare, competitive intelligence, and defense.
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