学历文凭
Masters Degree
专业院系
数据库管理
开学时间
课程时长
课程学费
国际学生入学条件
Unconditional Admission Status
For all other programs, must have a cumulative grade point average of 2.5 or above out of a 4.00 system
Mail or email a copy of your immigration documents:
Passport
I-20 from current school (if you have one)
U.S. Visa (if you have one)
I-94 (if you have one)
Minimum English Requirements (must meet one of the following)
A score of 550 or higher on the written TOEFL
A score of 210 or higher on the computerized TOEFL
A score of 79 or higher on the internet-based TOEFL
A score of Band 6.0 (overall) on the IELTS (International English Language Testing System)
A score of 51 or higher on PTE (Pearson Test of English)
A score of 100 or higher on Duolingo
Completion of Level 112 at an ELS Language Center or its equivalent
Completion of EF Level 5
If your English scores are below the required minimum for admissions, you may consider:
Retaking your English proficiency exam
IDP—雅思考试联合主办方
雅思考试总分
6.0
了解更多
- 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:A score of 51 or higher on PTE (Pearson Test of English)<br>A score of 100 or higher on Duolingo
课程简介
The Master of Science in Computer and Information Science (MCIS) program at the Southern Arkansas University is one of the largest, most affordable and highly attractive computer science graduate programs in the USA. The program offers a wide spectrum of online and onsite courses that are carefully designed to train the students in both theories and applications. The curriculum is constantly reviewed and updated to reflect the ongoing changes in the computer science field. The faculty members are highly qualified - many with extensive industry experience.<br><br>Students in the MCIS program can either study general topics in computer science or, based on their background and interest, pursue one of the following focus areas:<br><br>Data Science<br>Cyber Security & Privacy<br>The Data Science option focuses on data analytics, decision theories and big data. Students opting for this option are expected to have background in programming and basic statistics. Key career options include: data analyst, data scientist, data architect, data administrator, decision analyst, machine learning engineer, or pursuing doctoral studies.
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