Chi tiết khóa học Master of Science in Applied Data Science, , University of Southern California

Master of Science in Applied Data Science

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3

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The USC Viterbi Master of Science in Applied Data Science will train students as data scientists. This degree provides students with the knowledge and skill to solve real-world world challenges that require a combination of data management and data analytics skills. Students will learn how to use the latest big-data infrastructures, such as Hadoop and Spark. They will learn how to use the various analytical tools, including machine learning, data mining and data visualization. And students will learn how to apply these tools to real-world problems.



This degree is designed for students with a range of backgrounds, but students are expected to have at least a strong math and science background to pursue this degree. Students that do not have much training in computer science will first learn the basics of data science, including data formats, tools and techniques. They learn how to build data processing programs in Python, and they will learn how to apply the latest analytical tools through hands-on homework and projects. Students with a computer science background will be able to jump directly into the more advanced data science courses including data management, machine learning, data mining and statistics for data science. Once students have completed the introductory and core courses, they are given a choice of electives to allow them to pursue their own interests within data science.

Các hình thức học tập

Toàn thời gian (4 học kỳ)

Học phí
US$43,872.00 (1,108,864,810 đ) một năm
Ngày bắt đầu

Tháng Một 2027

Địa điểm

University Park Campus

3551 Trousdale Pkwy Los Angeles,

Los Angeles,

California,

90007, United States

Yêu cầu đầu vào

Dành cho sinh viên quốc tế

Applicants should have a bachelors degree from an accredited institution in any engineering or engineering-related discipline. We also accept applicants from majors including, but not limited to: Statistics, Mathematics, Computer Science, Information Systems, Economics, Information Technology, and Physics.

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