Program Length:
18 Months
Credit Hours:
30
Total Classes:
10
American University’s new online Master of Science in Data Science program was designed for working professionals seeking to build successful careers in data science. Our degree will give you the skills that employers want right now: a deep understanding of complex data, cutting-edge data science skills, strong communication and teamwork, and the ability to create data science-enabled solutions to real-life problems.
No technical background is necessary. American University’s 30-credit-hour (plus capstone) online program is designed for the working professional’s schedule and can be completed in 18 months.
With an MS in Data Science from AU, you will learn from leaders in their fields and acquire rigorous analytical training, along with creative problem-solving skills for success in industry, academia, nonprofits, and government.
AU’s Online MS in Data Science is designed to uniquely prepare students from different disciplines with any or no technical background to master both the theoretical knowledge and practical skills used by data scientists in academia, industry, and government and solve real-world problems involving complex data. Our online program can be completed in 1.5 years by taking summer courses. It balances students’ desire for flexibility with evening classes while mixing asynchronous and synchronous learning delivery, enabling interactions between instructors and students. Modern courses such as Natural Language Processing, Neural Networks and Deep Learning, and Business Intelligence will train our students to use cutting-edge technologies. Students will choose an applied field in which they will analyze data and explain the associated issues, culminating in the final semester capstoneexperience, DATA-793 Practicum, working directly with outside domain experts and faculty.
DS Knowledge
Create data science-enabled solutions using critical thinking to integrate domain knowledge with best practices and state-of-the-art methods from statistics and computer science. Design and develop useful models and relevant code-based analyses applicable to needs in government, industry, academia, and non-profits.
Responsible DS
Evaluate problems for potential ethical issues across the DS lifecycle. Apply best practice methods and algorithms to mitigate ethical risk. Ensure analysis and solutions are transparent, reproducible, and developed in accordance with professional codes of conduct.
Collaboration
Apply state-of-the-art human and technical collaboration methods and tools, as a team leader or team member, to engage and empower diverse teams to deliver high-quality project solutions while operating with constrained resources.
DS Lifecycle
Execute a repeatable data science lifecycle to engage stakeholders, collect, clean, and organize large amounts of data; develop, analyze, and test models; deploy solutions, and effectively communicate results and recommendations.
Community Engagement
Participate in the DS professional community as a knowledgeable practitioner aware of and engaged in diverse forums as a consumer and contributor.
DS Solutions
Demonstrate curiosity, creativity, and graduate-level competency through a portfolio of individual and group projects, based on large-scale real-world data, employing methods and techniques from across DS Specialities.
Upon completion of this program, students will be able to:
Demonstrate understanding of statistical and computational tools (including R) and advanced techniques for data analysis.
Process, understand, and explore a wide class of human-generated information to solve complex problems and produce new knowledge.
Demonstrate ability to effectively communicate understanding of data analytic techniques and statistical and computational tools.
Demonstrate ability to effectively communicate understanding of data analytic techniques and statistical and computational tools.
Apply knowledge of statistical and computational tools to political, social, and institutional problems for data analytic positions in academia, government, and industry.
Apply knowledge of statistical and computational tools to political, social, and institutional problems for data analytic positions in academia, government, and industry.
American University’s MS in Data Science seeks candidates who want to make a career change into Data Science. Online MS Data Science candidates must have a bachelor’s degree with a cumulative grade point average of 3.00 (on a 4.00 scale) from an accredited college or university to apply. Applicants must have completed one of the following:
STAT-202 Basic Statistics (4) or STAT-203 Basic Statistics with Calculus (4) or STAT-204 Introduction to Business Statistics (4). This may be waived for qualified persons with comparable prior education or experience. Students are required to complete a mathematical boot camp prior to starting the program.
GMAT and GRE scores are not required. The program will have three start dates throughout the year: January, May, and August. Applications are accepted, and admissions decisions are made on a rolling basis.
To complete your application, you must submit the following:
*for international applicants
Our online MS in Data Science program curriculum features 6 core courses and the opportunity to select a predesigned focus area or a range of electives to personalize your executions and meet your career goals.
Required (12 credit hours)
Required (3 credit hours)
Required (3 credit hours)
*All applicants will be automatically considered for scholarships, based upon merit. No separate application is required. Please note that scholarships are administered at the departmental level and not by the Office of Financial Aid. Please contact the admissions office or program director for further information.
Select one of two predesigned focus areas or create your own self-designed path by combining
electives from different areas. Focus areas include:
Required (6 credit hours)
Choose one of the below
Elective (3 credit hours)
Complete 9 credit hours from the following if not taken to
fulfill Analysis/Statistics, or other graduate courses
approved by advisor:
Learn more about some of our faculty members below:
Find out how we will help you achieve your short- and long-term professional goals.
Nearly every type of organization — from government, to retail, to healthcare — needs data scientists. Data science job growth is occurring across a variety of industries every year. In fact, U.S. Bureau of Labor Statistics predicts a 36 percent increase from 2021 to 2031 in data science roles annually through the next decade.
As a data scientist, you’ll gather, clean, and organize large amounts of data for businesses and organizations. You could work for global corporations, small businesses, and other types of companies.
Research scientists are responsible for designing, undertaking and analysing information from controlled laboratory-based investigations, experiments and trials. You could work for government laboratories, environmental organisations, specialist research organisations or universities.
ML Engineer builds artificial intelligence (AI) systems that leverage huge data sets to generate and develop algorithms capable of learning and eventually making predictions. Each time the software performs an operation, it “learns” from those results to carry out future operations more accurately.
Data analysts are responsible for analyzing data using statistical techniques, implementing and maintaining databases, gathering data from primary and secondary sources, identifying, analyzing and interpreting trends from the data.
You will experience the AU advantage with small class sizes, real-world experience, and flexible scheduling. You will engage in live seminar-style discussions, where you can enter breakout rooms for smaller discussions with classmates or one-on-one sessions with your professor. Personal attention will be provided throughout your course of study: in coursework, research, intellectual development, and career development. You will gain real world experience for six months of the program tackling data science and analytics problems at organizations around the DMV Area and beyond. Thus, students will be exposed to different research opportunities and internships and be much more competitive for jobs requiring deep understanding of the methods in data science.
57%
Male
43%
Female
31%
Non-White
36%
International Students
American University’s Kogod School of Business is dedicated to
supporting military service members, veterans, and their families.
Military-connected students are able to apply their VA education
benefits when they enroll, including the Post-9/11 GI Bill, the
Montgomery GI Bill (MGIB), Tuition Assistance (TA), and the Yellow
Ribbon Program for those who qualify.
As an online MS Data Science student, you can earn your degree no matter where you live or are stationed—and translate your military
American University’s Kogod School of Business is dedicated to supporting military service members, veterans, and their families.
Military-connected students are able to apply their VA education benefits when they enroll, including the Post-9/11 GI Bill, the Montgomery GI Bill (MGIB), Tuition Assistance (TA), and the Yellow Ribbon Program for those who qualify.
As an online MBA student, you can earn your degree no matter where you live or are stationed—and translate your military
experience and leadership skills into new career possibilities
across a variety of industries and organizations.
Applicants who have served in any branch of the U.S. military on active duty within the past three years are eligible to waive
their application fee.
experience and leadership skills into new career possibilities across a variety of industries and organizations.
Applicants who have served in any branch of the U.S. military on active duty within the past three years are eligible to waive their application fee.
Learn more about how to apply for military benefits.
Learn more about how our online program can set you up for career success.
Cookie | Duration | Description |
---|---|---|
cookielawinfo-checkbox-analytics | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics". |
cookielawinfo-checkbox-functional | 11 months | The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". |
cookielawinfo-checkbox-necessary | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary". |
cookielawinfo-checkbox-others | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other. |
cookielawinfo-checkbox-performance | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance". |
viewed_cookie_policy | 11 months | The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data. |