数据科学理学硕士
Master of Science in Data Science

学历文凭
Professional Masters Degree

专业院系
数据处理技术

开学时间

课程时长

课程学费

国际学生入学条件
An undergraduate degree in Computer Science from an accredited university with a GPA greater than or equal to 3.25 (out of 4).
Language Proficiency in : (C/C++, Java) or (Python - Perl) and a Unix/Linux Shell. Courses in an accredited university with an equivalent grade of B or better in Multivariate Calculus, Discrete Math, Linear Algebra, Statistics, Probability. Students with undergraduate degrees in Statistics, Mathematics, Physics, Engineering and other Sciences with a GPA above 3.5 (out of 4) , may be considered for temporal admission and will be placed in undergraduate bridge classes on Data Structures and Algorithms, Data Bases, Operating Systems and Computer Architecture. After successful completion of these remedial classes (with a grade of B or better) they will be granted full admission into the MSDS Program.
The Graduate School generally expects successful applicants to have verbal and quantitative Graduate Record Exam scores of at least 500/153 and 600/148, respectively (score scale for tests taken before/after August 1, 2011). Successful applicants to the MSDS program are likely to have quantitative scores considerably higher than 600/148. For students submitting GMAT scores, the typical requirements are a verbal score of at least 29 and a quantitative score of at least 41. However, there is often some flexibility for the verbal score for both GRE and GMAT.
The minimum paper-based TOEFL score is 550. The minimum computer-based TOEFL score is 213
The minimum IBT-internet based TOEFL is Writing 22, Speaking 23, Reading 21, Listening 17.( Totel iBT) - 83
An acceptable IELTS score is bandwidth 7.
Language Proficiency in : (C/C++, Java) or (Python - Perl) and a Unix/Linux Shell. Courses in an accredited university with an equivalent grade of B or better in Multivariate Calculus, Discrete Math, Linear Algebra, Statistics, Probability. Students with undergraduate degrees in Statistics, Mathematics, Physics, Engineering and other Sciences with a GPA above 3.5 (out of 4) , may be considered for temporal admission and will be placed in undergraduate bridge classes on Data Structures and Algorithms, Data Bases, Operating Systems and Computer Architecture. After successful completion of these remedial classes (with a grade of B or better) they will be granted full admission into the MSDS Program.
The Graduate School generally expects successful applicants to have verbal and quantitative Graduate Record Exam scores of at least 500/153 and 600/148, respectively (score scale for tests taken before/after August 1, 2011). Successful applicants to the MSDS program are likely to have quantitative scores considerably higher than 600/148. For students submitting GMAT scores, the typical requirements are a verbal score of at least 29 and a quantitative score of at least 41. However, there is often some flexibility for the verbal score for both GRE and GMAT.
The minimum paper-based TOEFL score is 550. The minimum computer-based TOEFL score is 213
The minimum IBT-internet based TOEFL is Writing 22, Speaking 23, Reading 21, Listening 17.( Totel iBT) - 83
An acceptable IELTS score is bandwidth 7.
IDP—雅思考试联合主办方

雅思考试总分
7.0
了解更多
- 雅思总分:7
- 托福网考总分:83
- 托福笔试总分:550
- 其他语言考试:NA
CRICOS代码:
申请截止日期:请 与IDP联系 以获取详细信息。
课程简介
这个数据科学专业的硕士课程不仅仅是适应大数据的出现,而是一个全新设计的分析学位课程,重点关注最新的系统,工具和算法来存储,检索,处理,分析,可视化,并合成大数据。它包括六个基础班和六个选修课。每个学生都必须在毕业前完成一个竞争性的一学期Capstone项目。该程序的主要目标是构建以一致的方式集成整个数据周期的系统:从数据收集到数据可视化和计算机人机交互辅助的数据合成。
This Professional Master program in Data Science, rather than just adapting to the advent of Big Data, is an analytical degree program designed from the ground up to focus on the latest systems, tools, and algorithms to store, retrieve, process, analyze, visualize, and synthesize large data. It consists of six foundational classes and six elective courses. Every student is required to complete before graduation a competitive one semester Capstone Project. A central goal of the program is to build systems that integrate in a coherent manner the full data cycle: from data gathering to data visualization and data synthesis aided by computer-human interaction.
This Professional Master program in Data Science, rather than just adapting to the advent of Big Data, is an analytical degree program designed from the ground up to focus on the latest systems, tools, and algorithms to store, retrieve, process, analyze, visualize, and synthesize large data. It consists of six foundational classes and six elective courses. Every student is required to complete before graduation a competitive one semester Capstone Project. A central goal of the program is to build systems that integrate in a coherent manner the full data cycle: from data gathering to data visualization and data synthesis aided by computer-human interaction.
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168
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