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Master of Science in Data Science
在舊金山大學
關於課程
USF’s one-year Master of Science in Data Science (MSDS) program delivers a rigorous curriculum focused on mathematical and computational techniques in the field of data science. The curriculum emphasizes the careful formulation of business problems, selecting effective analytical techniques to address those problems, and communicating solutions in a clear and creative fashion. All students gain real world experience for nine months out of the twelve month program (15 hours/week) tackling data science and analytics problems at companies around the San Francisco Bay Area and beyond.
Students will- Possess a theoretical understanding of classical statistical models (e.g., generalized linear models, linear time series models, etc.), as well as the ability to apply those models effectively. Possess a theoretical understanding of machine learning techniques (e.g., random forests, neutral networks, naive Bayes, k-means, etc.), as well as the ability to apply those techniques effectively. Effectively use modern programming languages (e.g., R, Python, SQL, etc.) and technologies (AWS, Hive, Spark, Hadoop, etc.) to scrape, clean, organize, query, summarize, visualize, and model large volumes and varieties of data. Prepare for careers as data scientists by solving real-world, data-driven, business problems with other data scientists, and understand the social, ethical, legal, and policy issues that increasingly challenge and confront data scientists.
Students will- Possess a theoretical understanding of classical statistical models (e.g., generalized linear models, linear time series models, etc.), as well as the ability to apply those models effectively. Possess a theoretical understanding of machine learning techniques (e.g., random forests, neutral networks, naive Bayes, k-means, etc.), as well as the ability to apply those techniques effectively. Effectively use modern programming languages (e.g., R, Python, SQL, etc.) and technologies (AWS, Hive, Spark, Hadoop, etc.) to scrape, clean, organize, query, summarize, visualize, and model large volumes and varieties of data. Prepare for careers as data scientists by solving real-world, data-driven, business problems with other data scientists, and understand the social, ethical, legal, and policy issues that increasingly challenge and confront data scientists.
- 實習機會
開始日期及學費
學費僅供參考。立即與我們的留學顧問聯繫了解最新資訊。
- 課程總長： 2 Semester(s)
- 費用: 無法取得
| In學年take | 位置 |
|---|---|
| Summer (May), 2024 | San Francisco |
| Summer (May), 2025 | San Francisco |
| Summer (May), 2026 | San Francisco |
如何申請
Entry requirements for 舊金山大學
Applicants who hold a bachelor's degree in any field and have fulfilled the MS in Data Science prerequisites are considered for admission. Completion of prerequisite courses for a grade at an accredited institution is strongly preferred. Applicants with academic or professional backgrounds in math, computer science, engineering, finance, economics or equivalent skills are encouraged to apply.
The statement of purpose is a one-to-two page statement that describes your educational and work experience as it relates to the MS in Data Science program, and your career goals.
Transcript (Academic Record)
Upload a copy of your transcript from each university and college attended. Please ensure the institution’s name and your name is on the document you upload. Transcripts from any schools and study abroad programs must be submitted since Bachelor's Degree institutions typically do not list transfer and study abroad courses with grades.
Statement of Purpose
The statement of purpose is a one-to-two page statement that describes your educational and work experience as it relates to the MS in Data Science program, and your career goals. You may also use this statement to explain any deficiencies in your academic record (e.g., failing or low grades in quantitative courses such as math, economics, computer science, or engineering, a low GPA in one semester, year, or degree program, lack of relevant coursework that is compensated by self-study or work experience, etc.), gaps in educational or employment history, reasons for low quantitative or verbal scores on the GRE or GMAT tests, and any other topics in your background and experience that you would like to address.
Letters of Recommendation
A minimum of two recommendation letters are required for your application (four maximum).
TOEFL INTERNET (IBT) – 90
IELTS – 6.5
English language requirements
托福(TOEFL iBT)總分: 90.0
最後申請期限:
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