国际学生入学条件
Two Letters of Recommendation A resume or outline describing at least the past five years of your employment history and any significant community, professional, or college extracurricular activities. Personal Statement , Transcripts from every accredited college or university attended (not just the degree granting institution) must be sent either to Pace University, directly from the academic institution electronically or by mail, or forwarded by the applicant in sealed envelopes from the academic institution.
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TOEFL scores of 78 (Internet-based version)
IELTS score of 6.5
Undergraduate grades required: 3.0 GPA (Grade Point Average)
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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:78
- 托福笔试总分:160
- 其他语言考试:Pearson PTE score of 52
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
In today's data-driven world, analytics is a part of everyday company operation. The difficult part is finding employees trained in data analytics with the skills to not only understand and utilize analytics tools but to follow up their analysis with clear, definitive recommendations for the next step. Successful data analysis pulls from many different skill sets. In order to determine what data to collect, you need to understand the business and market landscape so you can determine what data would suit your purpose. You need to know how to gather that data, what tools are the best to analyse it, how to translate the results into a story the CEO will understand, and how to use that data to make recommendations for enterprise-level decision making that will heavily impact the direction of the organization.<br><br>The career opportunities around Big Data have never been greater. The MS in Enterprise Analytics combines computer science, statistics, data warehousing, database design, and data mining into a program that includes advanced analytics skills, a foundation in data science technology architectures, database programming, and algorithmic thinking to source data, build queries, develop reports, and build enterprise applications that extract maximum value and recognize patterns or anomalies in Big Data sets.
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