Ready or not, we are living in a data-driven world. Every sector in our global economy is using data to make better management and policy decisions. The US Bureau of Labor Statistics projects a 36% increase in data science jobs from 2021 to 2031 — with DC having the nation's highest concentration of data science positions. Forbes and Glassdoor consistently rank Data Scientist at or near the top of all professions for job-satisfaction and median base salary at $120,000.
American University's MS program provides foundations, local networks, and flexibility to shape your career and course of study:
- Our program welcomes students from different disciplines with minimal technical background, who can succeed in new careers as Data Scientists — see admissions and coursework details.
- Diverse faculty help you build competence and confidence across a spectrum of data science methods and skills as students solve complex problems involving data.
- Students work both individually and in larger group projects in multiple courses, from Advanced Machine Learning and Deep Learning to Natural Language Processing and special topics classes, to analyze and model large, real-world data sets of their choice and then develop reports, presentations, interactive analyses, visualizations, and packages.
- Our project-based curriculum concludes with a Practicum where students work with outside domain experts and apply their data science skills and creativity to solve real-world problems that make a difference in our communities.
- The MS degree is jointly administered by AU's School of Public Affairs and College of Arts and Sciences, guided by an external advisory board to help you explore options and refine your expertise however you choose.
Program tracks for this degree include:
- Applied Public Affairs
- Business Analytics
- Computer Science
- Environmental Science
- International Economic Relations
- Investigative Journalism
- Microeconomic Analysis
While pursuing their primary track, students will master both the theoretical knowledge and practical skills used by data scientists in academia, industry, and government.
Core courses such as Statistical Machine Learning, Data Science, and Statistical Programming in R will train students to clean, process, visualize, and archive modern datasets, including text, imagery, and biometric data, apply machine learning algorithms to real data, and use the mathematical and statistical language of data scientists, leading to the DATA-793 Practicum, working directly with faculty and other researchers' ongoing projects.
Knowledgeable Faculty Dedicated to Your Success
Courses are taught by the same knowledgeable, innovative, and widely published professors who teach our master of arts, master of science, and undergraduate courses. You will learn the theories of data science and practical skills from respected experts in the field: Data Science Faculty.
Work, study, and make a difference in the nation's capital
Consistently ranked as one of the best cities for job seekers, Washington, DC, offers data scientists unparalleled access to private– and public–sector opportunities. AU's campus is minutes from industry giants such as Deloitte Consulting, Amazon, Booz Allen Hamilton, National Institutes of Health, BNY Mellon, Cambridge Associates, Lockheed Martin, and the Peace Corps. Our graduates start with a foot in the door, thanks to the university's institutional relationships with government agencies, locally-based companies, and nonprofit organizations.
Respected Positions in a Growing Field
Data scientists use their skills to find critical patterns and link them to business goals. They provide employers with such valuable insights. As a result, demand for data scientists is growing in nearly every sector. Data scientists are highly sought after and well paid. In this program, you will develop the skills to visualize and analyze data in any field. There are limitless applications for the skills you will gain from an MS in Data Science.
Marketable skills include how to
- Use Data Science methods to create ethical, data-driven solutions for real problems in diverse fields
- Integrate specialty domain knowledge with acumen in mathematics, statistics, and computing
- Develop reproducible analyses using modern statistical/programming methods and tools
- Collect, clean, and organize large amounts of data from open data sites, through APIs, via web scraping or from SQL-based databases
- Create meaningful visualizations and graphics of quantitative and categorical data
- Apply appropriate statistical methods to build, analyze, test, and validate models of large data sets
- Apply advanced regressions methods for multivariate regression
- Develop machine learning solutions using statistical and quantitative methods
- Build and deploy web-based apps for interactive analysis
- Communicate complex ideas on data and solutions to diverse audiences orally and in writing
- Conduct ethical reviews of data sources and applications to identify potential issues and solutions
- Collaborate as a member of a team to complete projects on time to the desired quality
- Code proficiently with R, Tidyverse, R Shiny, R Markdown, R Studio, Python, HTML, CSS, SQL
The program is open to all students with a bachelor's degree from an accredited institution that have a cumulative grade point average of at least a 3.00 (on a 4.00 scale). Students without sufficient mathematical background as determined by the program directors may be required to complete a mathematical boot camp prior to starting the program.
You can find information about application deadlines here.
Explore our MS in Data Science