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
Applicants who do not qualify for full matriculation and have an undergraduate GPA between 2.5 and 2.84, may be conditionally admitted at the discretion of the program director.
As data science is an interdisciplinary field, we welcome applicants from diverse professional backgrounds. However, applicants should have the following prerequisites:
One computer programming course
One college-level statistics course
Basic linear algebra
Basic database systems
Students with an insufficient background for direct admission into the Data Science M.S. program may be admitted if they take the required prerequisite course(s), with the approval of the director.
Submit GRE scores:
Graduates of foreign universities are required to take the GRE and submit their scores.
U.S. students with a GPA below 2.85 may, at the discretion of the dean, be asked to take the GRE or other diagnostic tests. Admission will be based upon consideration of test results, previous academic performance, and related employment, if applicable.
Copies of undergraduate transcripts for all schools attended. All final, official transcripts must be received prior to the start of your first semester.
Copy of college diploma or proof of degree
Official GRE scores, if required
IELTS score- 6.0
TOEFL (iBT) score- 79
IDP—雅思考试联合主办方
雅思考试总分
6.0
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- 雅思总分:6
- 托福网考总分:79
- 托福笔试总分:160
- 其他语言考试:Pearson PTE score- 53
课程简介
Learn to master the ever-growing mountain of crucial data that businesses across the globe need help managing and understanding. Prepare for a solid career in data analytics, data management, and more. The Data Science, M.S. is designed for students with a computer science or related background interested in pursuing data analytics, machine learning, visualization, and more. You'll learn how to employ data science concepts and methods to solve problems in business and scientific contexts and communicate these solutions effectively. You'll study computing theory, languages, and algorithms, and use mathematical and statistical models to formulate and implement data analyses and learn to apply them ethically.<br>Our practical curriculum incorporates case studies in advanced topics of computer architecture from classic and modern processors, including large-scale systems. You may also participate in sponsored research projects alongside faculty members from funding sources such as the Department of Defense.
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