USC Launches New Master's in Mathematical Data Science: Program Overview, Curriculum, and Admission Requirements

发布时间：Date: 2025-05-09 返回新鲜资讯Back to News

The University of Southern California's Dornsife College of Letters, Arts and Sciences has launched a new STEM-designated Master of Science in Mathematical Data Science program, designed to equip students with advanced mathematical skills and machine learning techniques to help graduates secure high-paying positions in the job market. The program spans four semesters, with core courses covering Mathematics of Machine Learning, Mathematical Statistics for Data Science, and Python for Data Science and Scientific Computing, along with electives in quantitative finance, optimization algorithms, and more, to comprehensively enhance students' practical and theoretical foundations. In terms of admission requirements, the program prefers applicants with a mathematics-related undergraduate background, requiring prerequisite coursework in multivariate calculus, linear algebra, and probability theory, with recommended knowledge in statistics, optimization, and programming. Applicants must submit three letters of recommendation, and GRE scores are not required. CheersYou（清柚教育） suggests that students interested in data science plan their profile enhancement in advance, closely monitor program updates, and prepare application materials early to get a head start.

USC has added a new STEM master's program in Mathematical Data Science. Students interested in data science should start paying attention to it.

The Data Science program at USC's Dornsife College of Letters, Arts and Sciences will help students master complex mathematical skills and machine learning techniques. Graduates will not only be qualified for higher-level (and higher-paying) positions upon entering the job market but will also possess valuable foundational knowledge.

Curriculum

The USC Mathematical Data Science master's program lasts four semesters, and students must complete at least 32 course units. Core courses include: Mathematics of Machine Learning, Mathematical Statistics for Data Science, Foundations of Mathematical Data Science, Statistical Consulting and Data Analysis, and Python for Data Science and Scientific Computing.

Core Curriculum

Mathematics of Machine Learning
Mathematical Statistics for Data Science
Foundations of Mathematical Data Science
Statistical Consulting and Data Analysis
Python for Data Science and Scientific Computing

Electives

Data Science with Python
Applied Probability
Analysis of Variance and Design
Introduction to Time Series
Mathematical Foundations of Statistical Learning Theory
Machine Learning in Quantitative Finance
Optimization Methods for Analytics
Blended Data Business Analytics for Efficient Decisions
Statistical Computing and Data Visualization
Applied Modern Statistical Learning Methods
Computational Solution of Optimization problems
Optimization: Theory and Algorithms
Analysis of Algorithms
Computational Molecular Biology

Admission Requirements

Applicants must hold a mathematics-related bachelor's degree. Prerequisite coursework includes multivariate calculus, linear algebra, and probability theory; recommended prerequisites are statistics, basic optimization knowledge, and Python/R programming. Three letters of recommendation are required, and GRE scores are not required. Only fall semester admission is accepted, with applications opening on September 1 and closing on February 15 of the following year.

3 letters of recommendation
A statement of purpose
A resumé or CV
Official transcripts
English Proficiency Test Scores (international applicants only)

预约申请规划Book Advisory Service