Master of Science in Data Science

休斯顿大学清湖分校

US

QS排名:

  • 学历文凭

    Masters Degree

  • 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

GPA of 3.0 in an undergraduate degree.
GRE Total Score of 290 (150 Quantitative). GMAT may be used in lieu of GRE.
GRE is not required for students with a Master or Ph.D. degree, or undergraduate with a Bachelor degree from an US university.
Official International English Language System (IELTS) scores of 6.0 or higher, TOEFL - scores of 79, TOEFL exam - 550 on the paper-based TOEFL exam,
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IDP—雅思考试联合主办方

雅思考试总分

6.0

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  • 雅思总分:6
  • 托福网考总分:79
  • 托福笔试总分:550
  • 其他语言考试:Official Pearson Test of English (PTE) scores of 53 or higher.
CRICOS代码:
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课程简介

Data science is the effective use of data to extract valuable information and solve problems. It incorporates multi-disciplinary theories and skills, including computer science, statistics, software engineering, and the application domains. Data science is one of the most favorable career paths for highly-skilled professionals from diverse backgrounds.<br>The University of Houston-Clear Lake's Master of Science in Data Science degree takes a modern, industrial-oriented and multi-disciplinary approach to prepare students for promising data science jobs in wide career paths, such as data scientist and engineer, business and data analyst, data and enterprise architect, etc.<br>The Data Science M.S. degree program is designated as a STEM subject but is designed for a wide range of undergraduate backgrounds, including those that are non-STEM. The Data Science program has a close tie with local businesses and industry to ensure the program balance, currency and relevance, and to provide industrial capstone projects to the student. The faculty body is student-oriented and maintains active research in data science-related areas, including data analytics, Internet of Things and blockchain. The plan in Data Science leads to the Master of Science degree. This plan is designed to equip students with the capability of integrating a wide spectrum of interdisciplinary knowledge and skills to uncover and utilize data to produce, apply and communicate value-adding intelligence for organizations and the society, in various key technical, analytical, architectural and managerial positions
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