Bachelor of Science in Computer Science - Computational Data Analytics
康涅狄格大学-Kaplan International
国际学生入学条件
International applicants should have college preparatory coursework in the core subjects of English (if offered), mathematics, physical science, and social science reflected throughout their high school academic careers. Students applying to the School of Engineering must have taken secondary school level physics and chemistry.
International applicants who have completed one year or more of full-time coursework at a post-secondary institution in the United States. The total amount of academic work completed must be officially graded by the registrar of that institution and have a cumulative GPA value of 3.0 or higher, excluding ESL curriculum.
International applicants who have received a degree from an international post-secondary institution whose language of instruction is English. Official documentation will be required from the institution's Registrar's office stating that the medium of instruction for the degree received was English.
International applicants who have achieved 510 or higher on the Evidence-Based Reading and Writing section of the SAT or 24 or higher on the English, Reading, and Composite on the ACT.
International English Language Testing System (IELTS), or Duolingo are required for International applicants whose primary language is not English. The minimum score requirement for the TOEFL is 550 (paper-based), 213 (computer-based), or 79 (internet-based), minimum score requirement for the IELTS exam is 6.5, minimum Duolingo score requirement is 100. Test scores must be sent directly to the University of Connecticut from the respective test provider.
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雅思考试总分
6.5
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- 雅思总分:6.5
- 托福网考总分:79
- 托福笔试总分:550
- 其他语言考试:Duolingo score requirement is 100
课程简介
This program produces graduates with a broad understanding of both computing principles and computing practice. The program emphasizes the fundamental computing models through the design and analysis of algorithms and software. Included in the program is coursework in a computing application area outside of the School of Engineering such as business or bioinformatics. The program is supported by study in mathematics, science, and engineering. Students gain hands-on experience in the laboratory courses accompanying classroom work, and develop design skills in course work beginning in the first two years. Design experience continues in junior and senior years in the areas of software engineering and in applications areas of the student's choosing, culminating in the one semester Senior Design Project course.<br><br>We live in an era of big data. In every domain of science and engineering voluminous data gets generated. Processing these datasets is a big challenge. A great deal of useful information is hidden in this data. Effective techniques are needed to unravel this information. For instance, the analysis of genomic data could lead to the discovery of causes for various diseases and subsequently the development of relevant drugs. Accurate weather forecasting is possible with the analysis of appropriate atmospheric data.<br><br>In this concentration, the students will be trained in analyzing various kinds of data. Examples include visual data, text data, sequence data, etc. The students will also be exposed to the principles of databases. Recently, Artificial Intelligence (and machine learning in particular) techniques have been employed to solve many challenging problems efficiently. Students will also get exposure to discrete optimization which lies at the core of decision making, i.e., Business Analytics.
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