数据科学理学硕士
Master of Science in Data Science

学历文凭
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
Minimum 3.0 cumulative GPA on a 4.0 scale
Bachelor's degree awarded from a regionally accredited institution
Submit official transcripts from all college and universities attended, one of which must show the conferral of a Bachelor's degree from a regionally accredited institution
Letters of recommendation
The minimum scores considered for full graduate admission to CDM are:
80 on the iBT of the TOEFL with a minimum score of 17 on each section
550 on the paper-based TOEFL test
6.5 on the IELTS test
Bachelor's degree awarded from a regionally accredited institution
Submit official transcripts from all college and universities attended, one of which must show the conferral of a Bachelor's degree from a regionally accredited institution
Letters of recommendation
The minimum scores considered for full graduate admission to CDM are:
80 on the iBT of the TOEFL with a minimum score of 17 on each section
550 on the paper-based TOEFL test
6.5 on the IELTS test
IDP—雅思考试联合主办方

雅思考试总分
6.5
了解更多
- 雅思总分:6.5
- 托福网考总分:80
- 托福笔试总分:550
- 其他语言考试:NA
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
数据科学理学硕士(以前是预测分析理学硕士)教会学生先进的技术和分析技能,以应对大数据分析的挑战。该学位培养了下一代数据科学领导者,他们可以分析大量数据并从复杂数据源中提取信息。该课程强调技术水平和实践经验,并为学生提供数据挖掘,统计,机器学习和大数据处理方面的高级技能。
The MS in Data Science (formerly the MS in Predictive Analytics) teaches students advanced technical and analytical skills to meet the challenge of big data analytics. The degree prepares the next generation of leaders in data science who can analyze massive amounts of data and extract information from complex data sources. The curriculum emphasizes technical proficiency and practical experience, and provides students with advanced skills in data mining, statistics, machine learning, and big data processing.
The MS in Data Science (formerly the MS in Predictive Analytics) teaches students advanced technical and analytical skills to meet the challenge of big data analytics. The degree prepares the next generation of leaders in data science who can analyze massive amounts of data and extract information from complex data sources. The curriculum emphasizes technical proficiency and practical experience, and provides students with advanced skills in data mining, statistics, machine learning, and big data processing.
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