*Based on 2026–2027 Boston University tuition and fees. Merit scholarship may reduce cost.
Develop In-Demand Data Analytics Skills
With data analytics needs influencing every major industry—including health care, tech, finance, communication, entertainment, energy, transportation, government, and manufacturing, to name some—there is significant growth in specialized data science and machine learning areas. The demand for skilled talent continues to outpace supply, with McKinsey Global Institute anticipating a shortfall of up to 250,000 data scientists through the decade.
The Master of Science in Applied Data Analytics (MSADA) program provides solid knowledge of data analytics and examines the presentation and applications of the latest industry tools and approaches within an academically rigorous framework. Emphasizing both data analytics and applied areas—including databases, applied machine learning, and large dataset processing methods—the MSADA curriculum provides a thorough immersion in concepts and techniques for organizing, cleaning, analyzing, and representing/visualizing large amounts of data. Students will be exposed to various database systems, data mining tools, data visualization tools and packages, Python packages, R packages, and cloud services. The knowledge of analytics tools combined with an understanding of data mining and machine learning approaches will enable students to critically analyze real-world problems and understand the possibilities and limitations of analytics applications.
There are two optional concentrations to choose from:
The MS in Applied Data Analytics is also available on campus in Boston. Learn more.
Curriculum
A total of ten courses (40 units) is required. Students exempted from the foundation courses will complete a total of eight courses (32 units).
Students not choosing a concentration must complete the foundation courses, core courses, and general electives. Students pursuing a concentration should review the requirements for AI & Machine Learning or Data Engineering.
Preparatory Labs
All students are enrolled in the following free, online, non-unit preparatory labs designed to strengthen their academic foundation and serve as a key resource for the degree program. Requirements for completion are assessed during the application process.
Qualified students may be exempt from one or both foundation courses based on previous academic background in information technology, computer science, and mathematics. Applicants will be notified of their curriculum requirements upon admission. If foundation courses are assigned, they must be completed within the first semester of study.
Core Courses
(Four courses / 16 credits)
Plus one course from the following:
And one course from the following*:
*If choosing to take both MET CS 688 and MET CS 699, one will be counted as a core course and the other as a general elective.
General Electives
(Four courses/16 units)
Students not choosing a concentration must complete four general electives. Students pursuing a concentration should review the requirements for AI & Machine Learning or Data Engineering.
When choosing electives, students should make sure that they have all prerequisites required by the selected course. Note that some courses may not be available in an online format.
Master’s Thesis Option
(Two courses/8 units)
Students have the option to complete a master’s thesis by taking two Master Thesis courses (8 units) in addition to the program’s ten course (40 units) requirement. The thesis must be completed within 12 months and is available to MS in Applied Data Analytics candidates who have completed at least four courses toward their degree (not including foundation courses) and have a grade point average (GPA) of 3.7 or higher. Students are responsible for finding a thesis advisor and principal readers within the department. The advisor must be a full-time faculty member; the principal readers may be part-time faculty. Department approval is required.
Learn about application requirements for BU MET graduate degree and certificate programs.
How You Benefit from a Boston University Education
A BU credential can help lay the foundation for career advancement and personal success.
Benefit from an average 24:1 student-to-instructor ratio.
Work closely with highly qualified faculty and industry leaders who have substantial backgrounds and achievements in data analytics, data science, data storage technologies, cybersecurity, artificial intelligence (AI), machine learning, software development, and many other areas.
Gain in-depth, practical experience with the latest technologies through case studies and real-world projects.
Experience a supportive online network, with courses developed and taught by PhD-level full-time faculty and professionals with hands-on expertise in the industry.
Learn from the best—BU MET’s Department of Computer Science was established in 1979 and is the longest-running computer science department at BU. Over the course of its existence, the department has played an important role in the emergence of IT at the University and throughout the region.
All graduate students are automatically considered for merit scholarships during the application process and nominated based on eligibility. Learn more.
Rankings & Accreditations
#12, Best Online Master’s in Computer Information Technology Programs
MET’s online master’s degrees in computer information technology are ranked #12 in the nation by U.S. News & World Report.
#2 Best Online Master’s in Data Analytics of 2026
BU MET’s MS in Applied Data Analytics is ranked #2 Best Online Master’s in Data Analytics Degree Programs for 2026 by TechGuide.
Graduate with Analytics Expertise
Graduates of Metropolitan College’s Applied Data Analytics master’s degree will be able to demonstrate:
Knowledge of the foundations of applied probability and statistics and their relevance in day-to-day data analysis.
The ability to apply various data visualization techniques using real-world data sets and analyze the graphs and charts.
Knowledge of web analytics and metrics, procuring and processing unstructured text/data, and the ability to investigate hidden patterns.
Knowledge-discovery skills using data mining techniques and tools over large amounts of data.
The ability to implement machine learning algorithms and recognize their pertinence in real-world applications.
Comprehensive knowledge of data analytics techniques, skills, and critical thinking, and an understanding of the possibilities and limitations of their applications.
“This program led me to my current position as a data scientist at Boston’s Massachusetts General Hospital, where I implement machine learning models to improve the hospital’s operational efficiency and support physicians with clinical research. I am immensely happy with my investment in graduate school, as it led me to many amazing opportunities!” Read more.
Melissa Viator (MET’23) Data Scientist, Massachusetts General Hospital MS, Applied Data Analytics
Advance Your Career
BU MET’s Applied Data Analytics master’s prepares you for a wealth of different roles, such as Data Science Analyst, Senior Emerging Tech Engineer, Solution Specialist, Senior Data Architect, Senior Strategy Product Manager, Senior Audit Analyst, Data Scientist, Economist, Business Intelligence Analyst, Chief Analytics Officer, and Analytics Manager.
Recent graduates have found job opportunities and career paths at companies such as:
Fidelity Investments
Akamai Technologies
Amazon Web Services (AWS)
Chi Alpha Campus Ministries
Deloitte Consulting
Drew University
McKesson
Olympus Americas
Travelers
Turiyatree Technologies
Take Advantage of Career Resources at BU MET
You will find the support you need in reaching your career goals through MET’s Career Development office, which offers a variety of job-hunting resources, including one-on-one career counseling by appointment for online students. You can also take advantage of tools and resources available online through BU’s Center for Career Development.
Eric Braude Associate Professor Director of Digital Learning, Computer Science Coordinator, Computer Information Systems
Lou Chitkushev Professor, Computer Science
Senior Associate Dean, Academic Affairs
Director, Health Informatics & Health Sciences
Head, Digital Forensics Research Laboratory
Maryan Rizinski Associate Professor of the Practice, Computer Science
Anatoly Temkin Assistant Professor Emeritus, Computer Science
Ming Zhang Assistant Professor, Computer Science Coordinator, BSCS Programs
Yuting Zhang Assistant Professor, Computer Science Director, Cybersecurity Coordinator, Computer Systems & Digital Forensics
Tanya Zlateva Dean, Metropolitan College & Extended Education Professor of the Practice, Computer Science and Education Education Director, Information Security, Center for Reliable Information Systems & Cyber Security
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