国际学生入学条件
The Committee welcomes applications from candidates with relevant undergraduate/master's degrees and candidates with work or research experience in data science. Relevant degrees include mathematics, statistics, computer science, engineering, and other scientific disciplines that develop skills in drawing inferences or making predictions using data. Coursework or equivalent experience in calculus, probability, statistics and programming are required.
Academic Transcripts
Test Scores (if required)
Applicant Statements
R'sum or Curriculum Vitae
Letters of Recommendation, and
For the TOEFL/IELTS, we recommend a minimum score of 100 (TOEFL iBT) or an overall band score of at least 7 (IELTS). Applicants with lower scores may still apply.
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雅思考试总分
7.0
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- 雅思总分:7
- 托福网考总分:100
- 托福笔试总分:160
- 其他语言考试:NA
课程简介
Advances in computational speed and data availability, and the development of novel data analysis methods, have birthed a new field: data science. This new field requires a new type of researcher and actor: the rigorously trained, cross-disciplinary, and ethically responsible data scientist. Launched in Fall 2017, the pioneering CDS PhD Data Science program seeks to produce such researchers who are fluent in the emerging field of data science, and to develop a native environment for their education and training. The CDS PhD Data Science program has rapidly received widespread recognition and is considered among the top and most selective data science doctoral programs in the world. It has recently been recognized by the NSF through an NRT training grant.The CDS PhD program model rigorously trains data scientists of the future who (1) develop methodology and harness statistical tools to find answers to questions that transcend the boundaries of traditional academic disciplines, (2) clearly communicate to extract crisp questions from big, heterogeneous, uncertain data, (3) effectively translate fundamental research insights into data science practice in the sciences, medicine, industry, and government, and (4) are aware of the ethical implications of their work.Our programmatic mission is to nurture this new generation of data scientists, by designing and building a data science environment where methodological innovations are developed and translated successfully to domain applications, both scientific and social. Our vision is that combining fundamental research on the principles of data science with translational projects involving domain experts creates a virtuous cycle: Advances in data science methodology transform the process of discovery in the sciences, and enable effective data-driven governance in the public sector. At the same time, the demands of real-world translational projects will catalyze the creation of new data science methodologies. An essential ingredient of such methodologies is that they embed ethics and responsibility by design.
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