大数据分析哲学博士
Doctor of Philosophy in Big Data Analytics
  • 学历文凭

    Ph.D.

  • 专业院系

    数据处理技术

  • 开学时间

  • 课程时长

  • 课程学费

    汇率提示

国际学生入学条件

A Bachelor's degree or its equivalent in statistics, data analytics or a related field from an accredited U.S. institution recognized by UCF or its equivalent from a foreign institution.
The GRE is not required for admission to this program.
A current curriculum vitae.
A personal statement identifying the area of research interest and a description of the applicant's academic and professional experiences.
Three letters of recommendation.
The student should have a minimum cumulative GPA of 3.0 for all bachelor's level work completed.
Applicants to this program, except those that have earned or will earn a Masters or Doctoral degree from an accredited U.S. institution recognized by UCF, who have attended a college/university outside the United States must provide a course-by-course credential evaluation with GPA calculation.
Minimum UCF Requirement for TOEFL/IELTS
TOEFL iBT score of 80
IELTS band score of 6.5
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雅思考试总分

6.5

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  • 雅思总分:6.5
  • 托福网考总分:80
  • 托福笔试总分:160
  • 其他语言考试:NA
CRICOS代码:
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课程简介

大数据分析将培训具有统计学背景的研究人员,以分析海量,结构化或非结构化数据,以发现隐藏的模式,未知的相关性以及可用于做出更好决策的其他有用信息。该计划将为与大数据分析相关的主要方法(如预测分析,数据挖掘,文本分析和统计分析)提供强大的基础,并结合了统计学和计算机科学的优势。它将侧重于统计计算,统计数据挖掘及其在商业,社会和健康问题上的应用,并辅之以正在进行的产业合作。该计划的范围专门用于准备数据科学家和数据分析人员,他们将使用常规和新开发的统计方法处理非常大的数据集。
Big Data Analytics will train researchers with a statistics background to analyze massive, structured or unstructured data to uncover hidden patterns, unknown correlations and other useful information that can be used to make better decisions.<br><br>The program will provide a strong foundation in the major methodologies associated with Big Data Analytics such as predictive analytics, data mining, text analytics and statistical analysis with an interdisciplinary component that combines the strength of statistics and computer science. It will focus on statistical computing, statistical data mining and their application to business, social, and health problems complemented with ongoing industrial collaborations. The scope of this program is specialized to prepare data scientists and data analysts who will work with very large data sets using both conventional and newly developed statistical methods.
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