国际学生入学条件
Statement of Purpose
Transcript(s)
TOEFL/IELTS/PTE (international graduate students)
Letters of Recommendation (3)
Graduate Record Examination (GRE) (optional)
GRE Subject (optional)
CV/Resume
Writing Sample (optional for Ph.D., not required for M.S.)
iBT TOEFL - 96 Overall (Speaking 22, Listening 24, Reading 26, Writing 24)
IELTS - 7 Overall (Listening 7, Reading 7, Writing 7, Speaking 6.5)
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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:96
- 托福笔试总分:160
- 其他语言考试:PTE - 68 overall (with 68 in writting)
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
The Computer Science Department's graduate program is ranked among the top in the nation and in the top ten among public universities. Both M.S. and Ph.D degrees are offered, and almost all full-time students receive financial aid in the form of assistantships, fellowships, and grants. The Department has strong research programs in the following areas: artificial intelligence, computer systems and networking, database systems, programming languages, software engineering, scientific computing, algorithms and computation theory, computer vision, geometric computing, graphics, human-computer interaction, and bioinformatics.<br><br>In recent years, we have seen a tremendous increase in the data available in the digital format, the World Wide Web being a prominent example, and this trend is expected to accelerate with the increasing proliferation of devices, ranging from genome sequencing machines to microscopic biomedical sensors, that are capable of capturing even the minutest details of our everyday world. The database group at the University of Maryland at College Park carries out a multi-faceted and diverse research agenda that focuses on exploring the data management challenges in a wide variety of environments. Some of the most important focus areas over the last few years include life sciences and biological databases, graph databases, sensor network data management, social network data management, mobile databases, P2P networks, and unstructured text databases. At the same time, the database group has continued innovating in the traditional data management topics such as managing and querying data warehouses, spatial databases, query processing and optimization, data streams, approximate query processing, and data mining.
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