数据科学经济学学士学位
Bachelor of Science in Data Science - Economics

科罗拉多州立大学-INTO USA

US

QS排名:

  • 学历文凭

    Bachelor Degree

  • 专业院系

    经济学

  • 开学时间

  • 课程时长

  • 课程学费

    汇率提示

国际学生入学条件

Submit your most recent transcripts or mark sheets. We will ask for additional materials if necessary. All decisions are provisional until a final, official transcript verifying graduation is received. Only transcripts sent directly from the school or stamped and sealed are considered official. If a record is not in English, a certified literal English translation must accompany the transcript.

High school performance, as reflected on a student's transcript(s), is an essential component of the admission decision for all freshman/first-year applicants and for transfer applicants with fewer than 30 post-high school credits.

High school transcripts for transfer applicants with more than 30 post-high school credits are considered only when needed to satisfy the admission requirement in mathematics.

All freshman/first year applicants and all transfers with fewer than 60 post-high school college credits must submit proof of high school graduation or equivalent prior to the start of their first semester of enrollment.

IELTS Academic - 6.0,TOEFL IBT -72, PTE Academic - 50
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雅思考试总分

6.0

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  • 雅思总分:6
  • 托福网考总分:72
  • 托福笔试总分:160
  • 其他语言考试:PTE Academic - 50
CRICOS代码:
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课程简介

专注于数据科学专业的经济学为学生提供了数据科学的技术和理论基础,同时也使他们能够专注于经济学。数据科学是通过数据分析发现的知识和见解。因此,它利用了计算机科学,数学和统计学。它已成为一个单独的字段,以响应来自启用Web的传感器和仪器,移动设备,Web事务以及为数据存储和分析提供计算能力的大量数据。现代数据的挑战不仅在于其规模庞大,而且还因为它越来越多样化且结构化。从这些数据中收集的信息正在彻底改变从保健政策到高能物理的各个领域。在本专业中,您将使用技术技能,理论和创造力来处理大型和复杂的数据集,以解决实际
Data Science is the discovery of knowledge and insight through the analysis of data. As such, it draws on the study of algorithms and their implementation from computer science, the power of abstraction and of geometric and topological formalism from mathematics, and the modeling and analysis of data from statistics. It has emerged as a separate field in response to the avalanche of data from web enabled sensors and instrumentation, mobile devices, web logs and transactions, and the availability of computing power for data storage and analysis. Modern data is challenging not only due to its large scale, but also because it is increasingly heterogeneous and unstructured. Information gleaned from this data none-the-less is revolutionizing diverse areas of human endeavor from health policy to high energy physics.
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401

数据源:泰晤士高等教育世界大学排名

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