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
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
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- 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
课程简介
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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