Mathematics MA, Data Science Emphasis
Program Overview
The Mathematics MA program at UMSL offers an emphasis in data science, providing students with advanced knowledge and skills in data analysis and modeling. The program's core courses cover essential data science principles, while elective courses allow students to specialize in areas such as machine learning and statistical computing. Graduates are prepared for careers as data scientists, analysts, and other data-driven professionals in various industries. The program employs interactive lectures, hands-on labs, and guided research to deliver its curriculum.
Program Outline
Degree Overview:
The Mathematics MA program at UMSL offers an emphasis in data science, designed for individuals with a strong foundation in mathematics or a related field with significant mathematical content. The program aims to provide students with advanced knowledge and skills in data science, preparing them for careers in industries that leverage data analysis and modeling.
Objective:
The program's objective is to provide students with a comprehensive understanding of data science principles and techniques, enabling them to analyze, interpret, and model data effectively. Graduates will be equipped to apply their knowledge to solve real-world problems in various fields.
Outline:
- Data-Science Core Courses (12 credit hours):
- Exploratory Data Analysis with R
- Mathematical Statistics I
- Mathematical Statistics II
- Nonlinear Optimization
- Statistical Methods in Learning and Modeling
- Elective Courses (15 credit hours):
- Bayesian Statistical Methods
- Introduction to Stochastic Processes
- Scientific Computation
- High-dimensional Data Analysis
- Statistical Computing
- Topics in Statistics and its Applications
- Topics in Computation
- Advanced Topics in Nonlinear Optimization
- Machine Learning
- Data Mining
Assessment:
The program uses various assessment methods to evaluate student learning and progress:
- Coursework: Regular assignments, quizzes, and exams within each course
- Projects: Practical projects that require students to apply their knowledge and skills to real-world data analysis problems
- Thesis (optional): For students pursuing the thesis option, a written thesis and oral defense are required.
Teaching:
The program employs a combination of teaching methods to deliver its curriculum:
- Interactive Lectures: Faculty members engage students through lectures that introduce concepts, theories, and techniques.
- Hands-on Labs: Practical laboratory sessions allow students to apply their knowledge and develop their analytical skills using real-world datasets.
- Guided Research: Students have the opportunity to work closely with faculty mentors on research projects, gaining hands-on experience in data science.
Careers:
The Mathematics MA degree with a data science emphasis prepares graduates for a wide range of career opportunities in data-driven industries, including:
- Data Scientist
- Data Analyst
- Statistician
- Machine Learning Engineer
- Data Science Consultant Graduates are qualified to work in various sectors, including finance, healthcare, technology, manufacturing, and government agencies.