phd data science boston university

Advisory Board

Azer Bestavros, PhD

Associate Provost for Computing and Data Sciences

Lindsay Farrer, PhD

Section Chief, Biomedical Genetics Boston University Chobanian & Avedisian School of Medicine

Patricia Hibberd, MD, PhD

Chair of Global Health Boston University School of Public Health

Ioannis Paschalidis, PhD

Director of the Rafik B. Hariri Institute for Computing and Computational Science and Engineering

Faculty Affiliates

The PHDS Program includes faculty affiliates from across Boston University including the School of Public Health,  Chobanian & Avedisian School of Medicine ,  Goldman School of Dental Medicine ,  College of Arts and Science ,  College of Engineering , and the  Hariri Institute for Computing . PHDS affiliated faculty have a wide range of expertise in data science including machine learning, artificial intelligence, data visualization techniques, deep learning, and reproducible research.

Industry Affiliates

The PHDS Program has partners from industry who are actively working in health data science. Industry affiliates enhance our program by sharing scientific questions and challenges they are confronting in industry and providing new opportunities for collaboration with our community. In addition, our industry affiliates may serve as mentors to students, providing training opportunities through mentored projects and internships.

Fully Funded PhD Programs in Data Science

As part of our series  How to Fully Fund Your PhD , here is a list of US universities offering fully funded PhD programs in Data Science. Data Science entails a combination of statistical analysis and data mining where researchers analyze data and build models using program languages such as R, Python, and SQL. Unlike computer science , which focuses on software engineering, data science aims to understand the data itself, uncover patterns, and use it to predict outcomes . A Data Science PhD opens opportunities for those aiming to advance their careers in academia, industry, research, and even create a startup initiative of their own.

“Full funding” is a financial aid package for full-time students that includes full tuition remission and an annual stipend or salary during the entire program, usually 3-6 years. To receive this funding, students will typically teach or complete a research project in their chosen subject. Considering fully funded programs is essential because not all universities grant funding to their doctoral students. By including smaller and lesser-known schools in your research, you optimize your chances of finding the perfect fully funded program for you.

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Northwestern University Fully Funded PhD in Statistics and Data Science

In Evanston, Illinois, Northwestern University offers a fully funded PhD in Statistics and Data Science. This comprehensive program equips students with knowledge of statistical theory, data science methodologies, and their versatile applications across diverse fields. The program offers financial support through university fellowships, teaching, and research assistantships. With a commitment to the academic journey, Northwestern ensures funding for five academic years and five summers, contingent on satisfactory academic standing.

Southern Methodist University Fully Funded PhD in Data Science

Southern Methodist University in Dallas, Texas, provides a fully funded PhD program in Data Science. Noteworthy for its strong interdisciplinary approach, the program adapts to the evolving interests of students and faculty. It aims to showcase the broad applicability of data science research across various disciplines. The program emphasizes that the future of data science spans beyond specific domains. Successful applicants enjoy a generous annual stipend and opportunities to serve as both research and teaching assistants.

William & Mary University Fully Funded PhD in Data Science

William & Mary University, based in Williamsburg, Virginia offers a fully funded PhD in Data Science. The Ph.D. track is offered as a specialization within Applied Science, with the core mission of training students in the use of exceptionally large, heterogeneous datasets to drive decision-making across a wide range of fields (from Physics to the social sciences). Graduate students complete a core sequence of coursework as a cohort, and then work closely with an advisory committee to complete the degree program.  Competitive stipends and tuition are provided to selected students (stipends for AY23-24 are $29,000).

Boston University Fully Funded PhD in Computing & Data Sciences

Boston University in Massachusetts provides a fully funded Computing & Data Sciences PhD. This program focuses on solving problems and synthesizing knowledge related to systematic, generalizable, and scalable extraction of insights from data. It also highlights the design of new information systems and products for actionable use of insights across diverse application domains. The funding model ensures five years of stipend support of $43,000 annually, a 100% tuition scholarship, and a health insurance credit for PhD students in good standing.

Yale University Fully Funded PhD in Statistics and Data Science

Yale University, New Haven, Connecticut, offers a fully funded PhD in Statistics and Data Science. The program encompasses key areas such as statistical theory, probability theory, information theory, bioinformatics and genetics, classification, data mining and machine learning, neural nets, network science, optimization, statistical computing, and graphical models and methods. Admission typically includes full tuition and a generous stipend for five years. Students commonly serve as teaching assistants and receive dissertation fellowships in their final year to focus on their research.

New York University Fully Funded PhD in Data Science

New York University provides a fully funded Ph.D. in Data Science. This innovative program aims to cultivate researchers fluent in the emerging field of data science within a nurturing educational environment. Students will engage with a broader range of fields under the guidance of interdisciplinary faculty. Successful candidates are assured financial support, including tuition coverage and a competitive stipend for up to five years during the fall and spring semesters. Additionally, CDS offers entrepreneurship workshops and a one-time award to cover prospective start-up expenses.

University of Virginia Fully Funded PhD in Data Science

The University of Virginia, located in Charlottesville, VA, offers a fully funded PhD in Data Science. This program equips students with the skills and knowledge needed for research and discovery in data science methods. PhD students receive financial support from the School of Data Science throughout their enrollment, covering full tuition, fees, and the premium for single-person coverage. Students may also receive a fellowship, research assistantship, or teaching assistantship, providing annual living support of approximately $33,000 per year.

University of Nevada Reno Fully Funded PhD in Statistics and Data Science

The University of Nevada-Reno, in Reno, Nevada, presents a fully funded PhD in Statistics and Data Science. This program is crafted to provide comprehensive training in modern statistics, focusing on extracting knowledge from data. With interdisciplinary research and a focus on computational skills, students are prepared to pursue a wide variety of jobs. Students accepted into the Statistics and Data Science PhD program receive a stipend of $2,200, a tuition waiver, and a subsidized medical plan. Additionally, students have the opportunity to pursue departmental and University-wide scholarships.

Stanford University Fully Funded PhD in Biomedical Data Science

Stanford University, in California, offers a fully funded PhD in Biomedical Data Science. This intellectually rigorous program emphasizes research in novel computational methods, including biomedical informatics, biostatistics, AI/ML, generative AI, and foundation models, with the aim of advancing biology and medicine. All PhD students receive full funding that covers tuition, stipend, and health insurance.

University of Tulsa & Team8 Cyber Fellows

The University of Tulsa & Team8 Cyber Fellows present a fully funded PhD position, providing a unique opportunity for students aspiring to advance research and development in cyber, data science, and machine learning. This collaborative initiative merges TU’s College of Engineering & Natural Sciences with Team8’s expertise in company-building, fostering an environment to address real-world industry challenges and translate cutting-edge research into innovative start-ups. Successful candidates will enjoy full tuition remission, a competitive living stipend, potential summer internships, and the perks associated with university graduate student employment while actively engaging with TU faculty on transformative projects.

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Computing & Data Sciences

Innovation and collaboration begin here., earn an ms in data science at bu.

Businesses, nonprofits, and governments need skilled and confident data analysts, engineers, and specialists to guide their decision-making. Meet the demand with Boston University’s new Master of Science in Data Science (MSDS) program— designed to be completed in as few as 9 months !

Enter a High-Growth, High-Paying Field

Thanks to the rise of artificial intelligence and machine learning, data science is one of the decade’s most dynamic fields, with high salaries and plenty of job security to go around.

Learn Where Innovation Begins

We talk the talk. No gas. No fuels. No emissions. Earn your master’s in BU's most environmentally sustainable, energy-efficient structure—the striking 19-story Center for Computing & Data Sciences building, designed to defy convention and spark collaboration.

PhD in Data Science

One of the first programs of its kind, in the nation, WPI’s interdisciplinary PhD in Data Science recognizes that traditional data processing applications can no longer handle today’s large and complex datasets. New models are needed to handle big data; and knowledgeable graduates with expertise in turning those observations into meaningful recommendations are in high demand.

Value Proposition Description

You’ll be working alongside faculty and industry partners to analyze, capture, search, share, store, transfer, query, and visualize huge amounts of data to solve real-world challenges. Some broad-stroke examples:

• using predictive analytics to identify cyber threats
• employing big data analytics to improve healthcare outcomes
• empowering “smart” cities to make data-driven policy changes critical for societal well-being

Applying to the Data Science PhD Program

Students applying to the data science PhD program will find WPI’s data science degree options listed with engineering, science, and mathematics on the application form.

WPI’s PhD in data science is interdisciplinary, drawing from Computer Science , Mathematical Sciences , and the Business School . Together, courses and dissertation research revolve around five key areas:

• Integrative Data Science
• Business Intelligence and Case Studies
• Data Access and Management
• Data Analytics and Mining
• Mathematical Analytics

PhD requirements include coursework as well as a research component. Together they total a minimum of 60 credit hours beyond the  Data Science master’s degree requirement . Students entering the Ph.D. Program with a bachelor’s degree first complete the M.S. in data science at WPI using the M.S.  Thesis  option as first step towards their Ph.D. degree. Each Ph.D. student is assigned an Academic Advisor and together they formulate a Plan of Study that then is approved by the Data Science Steering Committee.

• Core coursework requirements in the 5 categories as detailed below – 21 credits / 7 courses
• Electives in coursework – 9 credits / 3 courses
• Research credits – 30 credits TOTAL 60 credits (beyond MS program)

A Ph.D. student must obtain core competency by taking 7 courses from the below list of Data Science core areas, with an A grade in 4 out of the 7 courses and at least a grade B for the remaining 3 courses,  within 2 years after starting the Ph.D. 60 program.

Integrative Data Science  (Required) DS 501. Introduction to Data Science (3 credits)

Mathematical Analytics 3 credits (Select at least one) DS 502. Statistical Methods for Data Science (3 credits) MA 542. Regression Analysis MA 554. Applied Multivariate Analysis

Data Access and Management 3 credits (Select at least one) CS 542. Database Management Systems (3 credits) MIS571. Database Applications Development DS 503. Big Data Management (3 credits) CS 561. Advanced Topics in Database Systems

Data Analytics and Mining 3 credits (Select at least one) CS 548. Knowledge Discovery and Data Mining (3 credits) DS 504. Big Data Analytics (3 credits) CS 539. Machine Learning

Business Intelligence and Case Studies 3 credits (Select at least one) MIS 584. Business Intelligence MKT 568. Data Mining Business Applications

Nine more course credits must be taken, with the listing of courses pre-approved as electives for the Data Science program found in the WPI Graduate Catalog under  Data Science . Other graduate courses, graduate research credits, or ISGs may also be used, with prior approval of the Data Science Steering Committee. 

Two elective courses designed as ramp up courses for students who may be lacking in sufficient background in either statistics or programming, respectively, are listed below. They can count towards the 33 credits of the DS MS degree, However, they cannot be used to meet the above requirements in five core categories.

MA 511. Applied Statistics for Engineers and Scientists

CS 5007. Intro to Applications of CS with Data Structures and Algorithms (Programming for non-CS majors)

At least 30 credits must be research credits, consisting of DS 597 Directed Research and DS 699 Dissertation Research. Prior to Admission to Candidacy, a student may receive up to 18 credits of Pre-Dissertation Research under DS 597. Only after Admission to Candidacy by passing the Research Qualifier may a student receive credit toward Dissertation Research under DS 699.

As part of the research component, PhD students pass a Qualifying Examination and propose and defend Dissertation Research.  Learn more about the Ph.D. milestones, including the Ph.D. Qualifying Examination, the Ph.D. dissertation proposal and Ph.D. final dissertation defense.

Software Tools & Labs

The Data Science Innovation Lab is dedicated workspace for project work by students in the Data Science program. Robust servers and computer clusters are available for experimenting with large-scale datasets throughout labs at WPI, including many interdisciplinary facilities.

State-of-the-art software programs:

Close faculty interaction, cutting-edge equipment, and personal attention let you structure your program so it suits your individual career goals. You’ll leave with a degree that will help you succeed in your distinctive path.

Data science research gives you opportunities to work on grand challenge problems with societal importance, including topics such as cybersecurity, healthcare, and sustainability.

Our data science graduate program offers expertise in computer science, statistics, and business topics while giving you essential opportunities to work with industry partners.

WPI’s innovative and multidisciplinary graduate program prepares students to become talented and effective leaders in this rapidly evolving field.

WPI faculty and candidates in the PhD in data science are exploring every aspect of this burgeoning field. Together, they’re fueling breakthroughs that have direct, real-world impact in health, genetic analysis, sustainability, educational software, financial trading, and more.

A faculty advisor will help you design a Plan of Study for your dissertation as well as coursework in the core areas of data analytics and big data computing, statistical foundations and mathematical analytics, and business intelligence and innovation.

Cassandra DB2 Hadoop IBM Cognos IBM ILOG CPLEX IBM SPSS Modeler InfoSphere Big Insights InfoSphere Streams Mahout Maple MATLAB

MySQL Oracle Server Palisade DecisionTools Suite R RapidMiner SAS Spotfire SQL Server Tableaux Weka

Faculty Profiles

As founding Head of the interdisciplinary Data Science program here at WPI, I take great pleasure in doing all in my power to support the Data Science community in all its facets from research collaborations, and new educational initiatives to our innovative industry-sponsored and mentored Graduate Qualifying projects at the graduate level.

Professor Kong’s research interests focus on data mining and machine learning, with emphasis on addressing the data science problems in biomedical and social applications. Data today involves an increasing number of data types that need to be handled differently from conventional data records, and an increasing number of data sources that need to be fused together. Dr. Kong is particularly interested in designing algorithms to tame data variety issues in various research fields, such as biomedical research, social computing, neuroscience, and business intelligence.

Yanhua Li is an Associate Professor in the Computer Science Department and Data Science Program at Worcester Polytechnic Institute (WPI). His research interests focus on artificial intelligence (AI) and data science, with applications in smart cities in many contexts, including spatial-temporal data analytics, urban planning and optimization.

My research focuses on compressed sensing, machine learning, signal processing, and the interaction between mathematics, computer science and software engineering. My interests range from theoretical results to algorithms for tackling practical applied problems, and I enjoy problems most when mathematical results lead to efficient software implementations for big data. I am looking forward to working with students at all levels and backgrounds who share an interest in mathematics, software, or data.

I am Professor of Operations and Industrial Engineering at Worcester Polytechnic Institute (WPI), with courtesy appointments in Mathematical Sciences, Data Science, and Computer Science. I hold a Ph.D. in Industrial Engineering from the University of Pittsburgh. My objective is to use science and technology to assist real human need by improving systems that serve vulnerable peoples, such as refugees and asylum seekers, survivors of human trafficking, and children in the foster care system.

The Data Science Community

Getting Involved

We’re data scientists – we use tools of the trade and big data analytics to innovate. Follow department happenings and industry trends via our social media channels on  Facebook  and  LinkedIn .

Refer a Friend

Do you have a friend, colleague, or family member who might be interested in Worcester Polytechnic Institute’s (WPI) graduate programs? Click below to tell them about our programs.

Need to Earn a Master’s First? Explore Our Pioneering MS in Data Science

Not quite ready to apply for our data science PhD program since you first need to earn a master’s? Our pioneering master’s in data science dives into how to articulate findings into how to synthesize huge amounts of data and articulate findings into innovative solutions. WPI is one of a handful of universities that offers a MS in data science. Are you a working professional and prefer to study online? Our master’s in data science online makes it possible for you to advance your expertise from wherever you are conveniently online. Our core courses dive into the same on campus data-science essentials like analysis techniques, database management, and more. Maybe you’re excited about elevating your career in big data, but have questions about PhD data science salary and popular job titles. Check out our career information for data science.

Advance Your Data Science Skills with a Graduate Certificate

Individuals who know how to interpret and harness large amounts of data are in high demand and our graduate certificates are a perfect way to customize your data science skills and aspirations. Our on campus graduate certificate in data science enables students to select six courses that dive into mathematical analytics, data management, business intelligence, and more. Maybe you have a busy work-life balance and prefer to study online? Our online data science certificate brings world-class instruction right to you with flexible course offerings that enable you to enhance your data analytics skills.

Ready to Start Your Data Science Path?

If data intrigues you and you love the idea of finding patterns and revealing the information in massive amounts of data, a future in data science likely appeals to you. If you have your sights set on a PhD in data science, you can get started on the right academic path with a bachelor’s in data science . WPI’s bachelor’s program offers hands-on projects to increase your understanding of the field while giving you real skills you can use. If you’re majoring in another field, such as business or computer science, a minor in data science will give you a solid understanding of data science concepts. With a minor in data science, you’ll gain skills and learn how to apply them to your chosen discipline.

WPI is proud to be the recipient of not one, but two National Science Foundation Research Traineeship programs. The programs provide exceptionally talented graduate students with specialized training and funding assistance to join careers at the forefront of technology and innovation. The programs are for graduate students in research-based master's and doctoral degree programs in STEM. Learn more .

The BioPoint Program for Graduate Students has been designed to complement traditional training in bioscience, digital and engineering fields. Students accepted into one of the home BioPoint programs will have the flexibility to select research advisors and take electives in other departments to broaden their skills. BioPoint curriculum is designed to be individual, interactive, project-focused and diverse, and includes innovative courses, seminars, journal clubs and industrial-based projects. Learn more .

DiscoverDataScience.org

Data Science Degree Programs in Massachusetts

Massachusetts is one of the Northeast’s data science hubs thanks to its universities, major employers, and the lure of Boston. Your data science journey may lead you to programs at Harvard University, the University of Massachusetts, and Tufts University. Employers like Boston Consulting, General Electric, and Staples call Massachusetts home and often look for data scientists to evolve their businesses.

Boston’s rich history and diverse neighborhoods offer a great place for an aspiring data scientist to set up shop. Massachusetts is dotted with cities like Cambridge, Quincy, Springfield, and Worcester that feature career opportunities. The Bay State is also within short drives of neighboring cities like Albany, Hartford, Manchester, and Providence. Whether you are starting or continuing your career, Massachusetts presents opportunities for growth in the data science field.

Career Outlook for Data Scientists in Massachusetts

The Bureau of Labor Statistics (BLS) is optimistic about data science careers in Massachusetts. The state was given a location quotient of 1.06 compared to the national average of 1.0. This quotient is based on a comparison of the state’s concentration of data science jobs compared to the national concentration.

The state’s higher-than-average job opportunities for data scientists often come with great pay. As of May 2021, the annual mean wage for a data scientist in Massachusetts is $111,550 compared to the national median of $100,910 reported by the BLS. Data science-related positions like database architect ($140,540), statistician ($116,740), and information research scientist ($139,490) also have favorable mean salaries in Massachusetts.

The Massachusetts Department of Economic Research projects favorable growth through 2030 for industries that often employ data science professionals:

• Transportation and warehousing: 29% growth
• Information: 74% growth
• Data processing and related services: 15%
• Other information services: 58% growth
• Professionals, scientific, and technical services: 08%

You should keep in mind that Massachusetts has a relatively high cost of living that can cut into a data scientist’s salary. The state’s cost of living is rated 139 compared to a national average rate of 100. Housing in Massachusetts is particularly expensive with a median home cost of $392,600 far exceeding the $216,200 national median cost. A one-bedroom apartment in Massachusetts has an average rent of $1,274 per month compared to a $930 national average.

The abundance of Massachusetts data science jobs on popular job search sites means that you are entering a good market for your skills. In March 2019, Indeed listed 2,592 jobs for data scientists in Boston. Glassdoor featured 2,094 jobs in the data science field including positions at Apple, Cengage, and Wayfair. Companies like Amazon Web Services and QuantumBlack listed data science jobs in Boston on LinkedIn .

In order to be competitive for data science jobs in Massachusetts, you will need to demonstrate knowledge in the field. An undergraduate or graduate degree from an in-state university can set you apart from other applicants. The data science programs detailed below can help you chart a course to success in the field.

On-Campus Undergraduate Data Science Programs in Massachusetts

An undergraduate degree opens doors to data science careers throughout Massachusetts. The state’s colleges and universities are known more for graduate programs specific to the data science field. There are a few options for college students trying to develop skills for entry-level positions in the industry. Simmons University is a small Boston-based university with a B.S. in data science and analytics. Students looking to learn the ins and outs of data science can also pursue undergraduate and graduate degrees at the University of Massachusetts-Dartmouth.

University of Massachusetts-Dartmouth B.S. in Data Science

The Dartmouth campus of the University of Massachusetts trains future professionals along the state’s southern coast. High school students and current college students have multiple options for studying data science at this campus. UMass Dartmouth not only provides a four-year B.S. option but also an accelerated B.S./M.S. option and a standalone M.S. program. As you start your path toward a data science career, you can accrue the necessary skills through the B.S. program.

The data science major at UMass Dartmouth provides a prescribed four-year path for each student. During the first year, you balance criticial reading and writing courses with major-focused classes in calculus and programming. The second year includes four math courses in statistics and algebra along with software design and data analysis. Third-year students are able to select two elective classes in addition to coursework on algorithms and probability. UMass Dartmouth requires seniors to complete six electives and a senior capstone during their final year.

The admissions process for UMass Dartmouth starts with a completed application and application fee. To complete the application , you need to submit an official high school transcript and an official score for the ACT or SAT. Each student also needs to write a 500-word personal essay to demonstrate writing ability and desire to attend the university. UMass Dartmouth also accepts letters of recommendation as optional supplements to applications.

Massachusetts residents interested in the data science program receive reduced tuition compared to out-of-state residents. During the 2020-2021 school year , UMass Dartmouth listed a full-time tuition of $13,496 for state residents. The out-of-state resident rate for the same school year was $28,716. Tuition and fees can be reduced with the help of university scholarships . The university automatically considers first-year students for a series of scholarships that require a minimum GPA of 3.0, high test scores, and full-time enrollment. Student already enrolled at UMass Dartmouth can also apply for awards like the Bochenek Memorial Scholarship.

On-Campus Graduate Data Science Programs in Massachusetts

Data scientists around the world take advantage of graduate data science programs in Massachusetts. You can continue your exploration of data science through M.S. programs at Harvard University and Tufts University . The University of Massachusetts-Lowell offers an M.S. in Business Analytics that is an example of specialized data science study. The following programs offer a glimpse into what it takes to complete graduate courses in data science.

Northeastern University M.S. in Data Science

Northeastern University allows students to study, explore, and find data science work near its Boston campus. The M.S. in Data Science is a collaboration of the computer science and computer engineering departments. This combination of faculty members, facilities, and resources help engineering and computer science students get the most out of their studies.

Every student in the data science graduate program starts by selecting one course each in algorithms, data management, machine learning, and visualization. Northeastern University encourages students to connect data science to other disciplines by requiring three electives from other colleges including social sciences, business, and design. You can further bring the real world into your data science studies by participating in a co-op or internship with a local organization in your second year.

An online application and a fee up to $100 gets the admissions process started for this data science program. Students demonstrate their academic qualifications by submitting transcripts and resumes with their applications. The university asks students to submit three letters of recommendations and a statement of purpose to add color to their experiences. The graduate school also requires submission of official GRE scores with application materials.

A graduate degree in data science from Northeastern University can seem like a pricey investment. The average student in this program paid $51,200 in tuition for the 2020-2021 school year. You can reduce your short-term financial burden on the way to a successful career by reviewing the university’s graduate funding options . The Double Husky Scholarship is targeted at Northeastern University alumi who pay 75% of the tuition rate if accepted. The Dean’s Scholarship covers a third of tuition for recipients, while the Merit Scholarship reduces tuition by 25%. Scholarships funded by the National Science Foundation and the U.S. Department of Defense encourage data science students to pursue cybersecurity research.

On-Campus Data Science Ph.D. Programs in Massachusetts

Worcester Polytechnic Institute (WPI) has been teaching future engineers, researchers, and scientists since its founding in 1865. The school continues to evolve its academic programs with a Ph.D. in data science that is unique in the state. This program draws on WPI’s business, computer science, and math expertise to train the next generation of data scientists. Students in the doctoral program focus on advanced studies in integrative data science, business intelligence, data access, data analytics, and mathematical analytics.

The Ph.D. program differs from its master’s program by requiring an additional 10 graduate courses along with a dissertation. Every doctoral candidate must complete a graduate course called Introduction to Data Science. Students are then required to select six courses from the five aforementioned categories, covering topics like big data analytics and regression analysis.

Three electives round out the coursework necessary to advance to dissertation reach. These electives can be selected from approved data science options or other departments as approved by faculty advisors. The 30-credit research block includes up to 18 credits of pre-dissertation research, the qualifying exam, and a dissertation defense.

WPI requires all graduate student to submit an online application with a $70 application fee to be considered for admission. This application needs to feature transcripts from previous colleges, three recommendation letters, and a personal statement. GRE scores are recommended for domestic students and waived for graduates of WPI.

The graduate student tuition rate for the 2020-2021 school year was $1,513 per credit. Doctoral students can learn new skills while reducing their tuition burden by pursuing teaching and research assistantships . WPI also features the Graduate Assistance in Areas of National Need (GAANN) fellowship, which helps data science Ph.D. students pay for school to prepare them for careers in important fields. To put the program’s costs into perspective, WPI cites an average starting salary of $141,250 for data science graduates at companies like Amazon, Dow, and Kayak.

On-Campus Graduate Certificate Programs in Massachusetts

If you are already in a data science career, you may need to augment your skills with additional graduate courses. UMass Amherst features a certificate in statistical and computational data science that digs into the connection between raw data and analysis. This five-course certificate splits the work between computer science and statistics courses with at least two courses available per semester.

The required courses for all certificate students are a Python-focused introduction to numerical computing and a machine learning class. You are able to select up to two computer science courses covering natural language processing, algorithms, and data science systems. The certificate program also requires up to three courses in statistics, probability, and modeling. If you select one computer science course, you must complete three math courses.

UMass Amherst opens the certificate to current graduate students and non-degree students with bachelor’s degrees. The graduate admissions process includes completion of an application, official transcripts, a resume, a personal statement, and at least two letters of recommendation. A non-degree application is a simpler process that focuses on prior education and residency. You can pursue the non-degree path to bolster your resume and apply up to two courses to future graduate work at UMass Amherst.

During the 2020-2021 school year, UMass Amherst listed a per-credit tuition rate of $2,021 for in-state students. The out-of-state rate for graduate students was $3,848 per credit. The graduate school offers non-working fellowships and traineeships along with grants that may be applicable to certificate students.

Online Data Science Degree Programs in Massachusetts

You don’t need to live in Massachusetts to take advantage of its educational bounty. Data scientists with wireless connections can complete online degree programs from Massachusetts schools. There are several online data science degrees available to professionals and students who are balancing school with work.

The Merrimack College master’s program in data science requires completion of eight courses in just over one year. The M.S. in Applied Data Science from Bay Path University allows data science generalists and specialists to pursue distinct paths. Boston College also offers a graduate certificate in data analytics with four courses on the latest trends in data science. Massachusetts has a full range of online data science courses to meet your professional needs.

2021 US Bureau of Labor Statistics salary and employment figures for data scientists reflect national data, not school-specific information. Conditions in your area may vary. Data accessed January 2023.

Best Data Science Programs in Massachusetts

• Related Programs

Master's in Data Science

Master’s in data science program overview.

The Data Science master's program, jointly led by the  Computer Science  and  Statistics  faculties, trains students in the rapidly growing field of data science. 

Data Science lies at the intersection of statistical methodology, computational science, and a wide range of application domains.  The program offers strong preparation in statistical modeling, machine learning, optimization, management and analysis of massive data sets, and data acquisition.  The program focuses on topics such as reproducible data analysis, collaborative problem solving, visualization and communication, and security and ethical issues that arise in data science.

To earn the Master of Science in Data Science, students must complete 12 courses. This requires students to be on campus for at least 3 semesters (one and a half academic years). Some students will choose to extend their studies for a fourth semester to take additional courses or complete a master’s thesis research project.

SEAS will be hosting virtual information sessions this Fall for students interested in the Data Science program. Registration for these sessions is available on the  Admissions Events page for prospective graduate students .

Why pursue a master’s degree in Data Science?

With companies and organizations better able to capture data in a multitude of ways, data-driven decision making is changing the way businesses operate. Powerful analytics tools can model and predict how consumers will behave or markets will respond. Consequently, an understanding of data science is a 21st century job skill that can be beneficial in many different careers.

Data Science Degree Career Paths

Data Science career paths are flexible. There are different pathways to use data science skills.

• Data science professional - data analyst, database developer, or data scientist.
• Analytics-enabled jobs - functional business analyst or data-driven manager.

Data science professionals like data analysts can become qualified for a data science or data system developer role depending on where they deepen their expertise. By expanding knowledge in Artificial Intelligence, statistics, data management, and big data analytics, a data analyst can transition into a data scientist role. By building on existing technical skills in Python, relational databases, and machine learning, a data analyst can become a data system developer. 

Requirements

There are no formal prerequisites for applicants to this master’s program. However, successful applicants do need to have sufficient background knowledge of calculus, linear algebra and differential equations; familiarity with probability and statistical inference; fluency in at least one programming language such as python or R, and an understanding of basic computer science concepts. As Data Science is an interdisciplinary field, SEAS welcomes applicants with undergraduate training in a wide range of academic disciplines. 

• How to Apply

Learn more about  how to apply to the Data Science degree program  or  apply now .

What should a graduate of the Data Science program be able to do?

The design of the program is based on eleven learning outcomes developed through discussions between the computer science and statistics faculty:

Build statistical models and understand their power and limitations

Design an experiment

Use machine learning and optimization to make decisions

Acquire, clean, and manage data

Visualize data for exploration, analysis, and communication

Collaborate within teams

Deliver reproducible data analysis

Manage and analyze massive data sets

Assemble computational pipelines to support data science from widely available tools

Conduct data science activities aware of and according to policy, privacy, security and ethical considerations

Apply problem-solving strategies to open-ended questions

Financing Your Degree

Students typically finance their master’s degree program with a combination of loans, savings, family support, grants (from governments, foundations and companies), fellowships and scholarships. We recommend you visit the Harvard Kenneth C. Griffin Graduate School of Arts and Sciences (Harvard Griffin GSAS)  Funding and Financial Aid  website prior to your application to learn more about your options.

Teaching Fellowships

Approximately 15% of our students are paid Teaching Fellows, usually in the second year. TFing in the first semester is highly unusual. Teaching compensation is paid out at Harvard graduate student rates.

Master's in Data Science Leadership

In master's in data science.

• Thesis Info
• Secondary Field in Data Science
• Info for Current Students
• Alumni News
• Student Stories

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Khoury College of Computer Sciences

College of engineering, data science.

Our Master’s in Data Science program will provide you a comprehensive foundation in the skills and theory of data science, as well as the tools and experience to translate data into clear, innovative, and strategic insights.

Data has become one of the most critical tools in shaping our economy, society, and culture. In fact, for the fourth year in a row, Glassdoor named data scientist as the best job in America. Now more than ever, the world needs people who can understand this untapped resource and draw conclusions so vital to future success.

We developed our Master’s in Data Science with that in mind. As an interdisciplinary program between the Khoury College of Computer Sciences and the College of Engineering, you’ll develop comprehensive expertise in mathematics, computing, and data engineering so you can take your data career to the next level. That interdisciplinary aspect means you’ll receive robust, comprehensive exposure to the world of data science. Our elective courses will help you create a curriculum that’s unique to your own interests. And with a full spectrum of exciting co-op, research, and internship opportunities, you’ll gain even more real-world experience to help you emerge from your studies prepared for whatever and wherever data leads you next.

More Details

Unique features.

• Our program meets F-1 international student status requirements.
• This is an interdisciplinary program between Khoury College of Computer Sciences and the Department of Electrical and Computer Engineering in the College of Engineering.
• Courses are tailored toward technically or mathematically trained students.
• Elective courses allow you to explore what interests you.

Program Objectives

• Data Management : Ability to effectively utilize integrated databases for managing large-scale datasets.
• Machine Learning : Ability to effectively apply an appropriate machine-learning model to a problem.
• Analysis and Visualization : Ability to effectively communicate insights derived from data.

An MSDS degree enables you to collect data from numerous sources (databases, files, images) and integrate them into a form in which the data is fit for analysis. Students develop strong programming and analysis skills to explore data, produce summary statistics, perform statistical analyses; using standard data mining and machine-learning models for effective analysis. Students learn to work with both structure and unstructured data. The program provides you with the knowledge to manage, process, analyze, and visualize data at scale. You will learn about the limitations of machine learning and data mining methods as applied to real-world problems and communicate the advantages/disadvantages of the methods to non-data experts. Students will carry out the full data analysis workflow, including unsupervised class discovery, supervised class comparison, and supervised class prediction. They will learn how to properly summarize, interpret, and communicate the analysis of results. In this program you will develop methods for modeling, analyzing, and reasoning about data arising in one or more application domains such as social science, health informatics, web and social media, climate informatics, urban informatics, geographical information systems, business analytics, bioinformatics, complex networks, public health, and game design.

Career Outlook

Students who successfully complete their master's in data science are qualified to seek jobs as:

• Data scientist
• Machine learning engineer
• Applications architect
• Enterprise architect
• Data architect
• Infrastructure architect
• Data engineer
• Business intelligence developer
• Data analyst

Employees with data science expertise are sought out in every industry, not just in technology. "Data scientists are highly educated—88 percent have at least a master's degree and 46 percent have PhDs—and while there are notable exceptions, a very strong educational background is usually required to develop the depth of knowledge necessary to be a data scientist," reports KDnuggets, a leading site on Big Data.

Testimonials

Professor olga vitek, khoury college of computer sciences, looking for something different.

A graduate degree or certificate from Northeastern—a top-ranked university—can accelerate your career through rigorous academic coursework and hands-on professional experience in the area of your interest. Apply now—and take your career to the next level.

Program Costs

Finance Your Education We offer a variety of resources, including scholarships and assistantships.

How to Apply Learn more about the application process and requirements.

Requirements

• Online application and fee
• Transcripts from all institutions attended 
• Statement of purpose that should include career goals and expected outcomes and benefits from the program
• Recent professional resumé listing detailed position responsibilities
• Three letters of recommendation
• GPA minimums: 3.0 on a 4.0 scale, 8.0 on a 10.0 scale, or 80 on a 100 scale
• Official TOEFL (100 minimum) or IELTS (7.5 minimum) examination scores (international students only)
• GRE Optional

Are You an International Student? Find out what additional documents are required to apply.

Global Engagement Learn how our teaching and research benefit from a worldwide network of students, faculty, and industry partners.

Admissions Dates

Applicants must submit the online application and all required admission materials no later than the stated deadlines to be considered for admission. Admissions decisions are made on a rolling basis.

Industry-aligned courses for in-demand careers.

For 100+ years, we’ve designed our programs with one thing in mind—your success. Explore the current program requirements and course descriptions, all designed to meet today’s industry needs and must-have skills.

View curriculum

Co-op makes the Northeastern graduate education richer and more meaningful. It provides master’s students with up to 12 months of professional experience that helps them develop the knowledge, awareness, perspective, and confidence to develop rich careers. In addition to the esteemed faculty, many students enroll in the master’s programs largely because of the successful co-op program.

Graduate students typically have an experiential work opportunity following their second semester. This could be a 6- to 8-month co-op or a 3- to 4-month internship. Those who initially experience co-op may have the opportunity to seek an internship for the following summer, or vice versa.

Student participation in experiential education provides enhanced

• Maturity, responsibility, and self-knowledge
• Technical expertise
• Occupational information
• Job-seeking and job-success skills
• Networking opportunities with those in desired career paths

Northeastern’s co-op program is based on a unique educational strategy that recognizes that classroom learning only provides some of the skills students will need to succeed in their professional lives. Our administration, faculty, and staff are dedicated to the university’s mission to “educate students for a life of fulfillment and accomplishment.” Co-op is closely integrated with our course curriculum and our advising system. The team of graduate co-op faculty within the Khoury College of Computer Sciences provides support for students in preparing for and succeeding in their co-ops.

These multiple connections make co-op at Northeastern an avenue to intellectual and personal growth—adding depth to classroom studies, providing exposure to career paths and opportunities, and developing in students a deeper understanding that leads to success in today’s world.

Our Faculty

Northeastern University faculty represents a broad cross-section of professional practices and fields, including finance, education, biomedical science, management, and the U.S. military. They serve as mentors and advisors and collaborate alongside you to solve the most pressing global challenges facing established and emerging markets.

Michelle Borkin

Kylie Bemis

John Rachlin

Jeongkyu Lee

David Kaeli

By enrolling in Northeastern, you’ll be connected to students at our 13 campuses, as well as 300,000-plus alumni and more than 3,500 employer partners around the world. Our global university system provides you with unique opportunities to think locally and act globally and serves as a platform for scaling ideas, talent, and solutions.

Below is a look at where our computing and IT alumni work, the positions they hold, and the skills they bring to their organization.

Where They Work

What they do.

• Engineering
• Information Technology
• Business Development
• Entrepreneurship
• Program and Project Management

What They're Skilled At

• Software Development

Learn more about Northeastern Alumni on  Linkedin .

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Earning an ms in computer science without a cs background.

Where To Earn A Ph.D. In Data Science Online In 2024

Updated: Apr 3, 2024, 2:15pm

Data science is among the most in-demand skill sets in the modern economy. Data science professionals help businesses make decisions by creating analytical models, combining elements of math, artificial intelligence, machine learning and statistics.

If you want to pursue a high-paying data science career or teach data science at the college level, you may want to earn a terminal degree in the field. Online Ph.D. in data science programs allow you to advance your career while balancing other responsibilities at work or home.

We found two online data science programs that met our ranking criteria. Read on to learn more about these schools and find answers to frequently asked questions about data science.

Why You Can Trust Forbes Advisor Education

Forbes Advisor’s education editors are committed to producing unbiased rankings and informative articles covering online colleges, tech bootcamps and career paths. Our ranking methodologies use data from the National Center for Education Statistics , education providers, and reputable educational and professional organizations. An advisory board of educators and other subject matter experts reviews and verifies our content to bring you trustworthy, up-to-date information. Advertisers do not influence our rankings or editorial content.

• Over 3,868 accredited, nonprofit colleges and universities analyzed nationwide
• 52 reputable tech bootcamp providers evaluated for our rankings
• All content is fact-checked and updated on an annual basis
• Rankings undergo five rounds of fact-checking
• Only 7.12% of all colleges, universities and bootcamp providers we consider are awarded

Online Ph.D. in Data Science Option

Capitol technology university, national university.

Located just outside Washington, D.C., in South Laurel, Maryland, Capitol Technology University offers an online doctoral degree in business analytics and data science. The program includes a limited residency requirement: Students must complete a course in contemporary research in management on campus, during which they take a qualifying exam. The degree requires 54 to 66 credits, and students can graduate within three years.

All students must also complete a dissertation and an oral defense of their work. The program costs $950 per credit for both in-state and out-of-state learners. Retired and active duty military receive a tuition discount.

At a Glance

• School Type: Private
• Application Fee: $100
• Degree Credit Requirements: 54 to 66 credits
• Program Enrollment Options: Part-time
• Notable Major-Specific Courses: Management theory in a global economy; analytics and decision analysis
• Concentrations Available: N/A
• In-Person Requirements: Yes, for residency

Based in San Diego, California, National University (NU) offers a variety of online programs, including a Ph.D. in data science. NU’s program requires 60 credits and takes an estimated 40 months. NU aims for flexibility, delivering coursework asynchronously and offering a new start date each Monday. The curriculum comprises 20 courses covering data science principles and data preparation methods.

NU runs on the quarter system and charges $442 per quarter unit for graduate courses. The program does not include any in-person requirements.

• Application Fee: Free
• Degree Credit Requirements: 60 credits
• Notable Major-Specific Courses: Principles of data science, data preparation methods
• In-Person Requirements: No

How To Find the Right Online Ph.D. in Data Science for You

Consider your future goals.

A Ph.D. in data science makes sense if you want to become a college professor , conduct original research or compete for the highest-paying and most cognitively demanding business analytics and machine learning positions. If you plan to pursue other careers, you may not need a terminal degree in this field.

If you want to work in academia, make sure your chosen doctorate in data science includes a dissertation requirement. A dissertation allows you to perform original research and contribute to scholarship in your field before you graduate. In turn, you’ll get a sense of your chosen career and a head start on professional publication.

Understand Your Expenses and Financing Options

Per-credit tuition rates for the programs in our guide ranged from $442 to $950. A 60-credit degree from NU totals about $26,500, while the 66-credit option at Capitol Tech costs more than $62,000.

Private universities, including NU and Capitol Tech, tend to cost more than public schools. Graduate students at nonprofit private universities paid an average of $20,408 per year in 2022-23, according to the National Center for Education Statistics . Over the course of a typical three-year Ph.D. program, this translates to about $61,000. This roughly matches Capitol Tech’s tuition, while NU offers a more affordable program.

While a Ph.D. might help you land a lucrative role in the long run, the upfront investment is still significant. Make sure to fill out the FAFSA ® to access federal student aid. This application is the gateway to opportunities like scholarships, grants and loans. You can pursue similar opportunities through schools and nonprofit organizations.

As a doctoral student, you may be able to access graduate assistantships or stipends, but these are often reserved for on-campus students who teach undergraduates or assist professors with research.

Should You Enroll in a Ph.D. in Data Science Online?

Pursuing a Ph.D. in data science online suits a specific kind of learner. To decide if that’s you, ask yourself a few key questions:

• What’s my budget? In some cases, public universities allow students who exclusively enroll in online courses to pay in-state or otherwise discounted tuition rates. Even if you have to pay full price, distance learners generally save on costs associated with housing and transportation.
• What are my other commitments? Distance learning is often a good fit for parents and students who need to work full time while pursuing their degree. Learners with outside responsibilities might pursue a program with asynchronous course delivery, which eliminates scheduled class sessions.
• What’s my learning style? Distance learning requires a great deal of discipline, organization and time management. If you need external accountability or prefer the structure of a peer group or physical classroom, on-campus learning might offer a better fit.

Accreditation for Online Ph.D.s in Data Science

There are two important types of college accreditation to consider: institutional and programmatic.

Institutional accreditation is essential; it involves vetting schools to ensure the quality of their finances, academics, and faculty, among other areas. The Council for Higher Education Accreditation (CHEA) and U.S. Department of Education oversee the regional agencies that administer this process.

You should only enroll at institutionally accredited schools. Otherwise, you will be ineligible for federal financial aid. You can check a school’s accreditation status on its website or by visiting the directory on CHEA’s website .

Individual departments and degrees earn programmatic accreditation based on their curriculum, faculty and learner outcomes. However, this process has not been widely established for data science programs, so it shouldn’t make or break your enrollment decision. However, you can still keep an eye out for accreditation from the Data Science Council of America (DASCA).

Our Methodology

We ranked two accredited, nonprofit colleges offering online Ph.D.s in data science in the U.S. using 15 data points in the categories of student experience, credibility, student outcomes and affordability. We pulled data for these categories from reliable resources such as the Integrated Postsecondary Education Data System ; private, third-party data sources; and individual school and program websites.

Data is accurate as of February 2024. Note that because online doctorates are relatively uncommon, fewer schools meet our ranking standards at the doctoral level.

We scored schools based on the following metrics:

Student Experience:

• Student-to-faculty ratio
• Socioeconomic diversity
• Availability of online coursework
• Total number of graduate assistants
• Proportion of graduate students enrolled in at least some distance education

Credibility:

• Fully accredited
• Programmatic accreditation status
• Nonprofit status

Student Outcomes:

• Overall graduation rate
• Median earnings 10 years after graduation

Affordability:

• In-state graduate student tuition
• In-state graduate student fees
• Alternative tuition plans offered
• Median federal student loan debt
• Student loan default rate

We listed the two schools in the U.S. that met our ranking criteria.

Find our full list of methodologies here .

Frequently Asked Questions (FAQs) About Earning a Ph.D. in Data Science Online

Can i do a ph.d. in data science online.

Yes, you can. National University and Capitol Technology University both offer Ph.D. programs in data science that you can complete mostly or entirely online.

Is a Ph.D. worth it for data science?

It depends on your goals and circumstances. A Ph.D. in data science may be a good fit if you want to pursue a career in research or academia or compete for advanced, lucrative positions in business analytics, artificial intelligence or machine learning.

Is it okay to get a Ph.D. online?

Yes, as long as the program is accredited. Distance learning requires strong motivation and self-discipline, so it suits some students better than others.

Can you become a professor with an online Ph.D.?

Yes, you can. Online diplomas feature the same coursework and degree requirements as in-person degrees, and your degree won’t say “online”.

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Ph.D. Specialization in Data Science

The ph.d. specialization in data science is an option within the applied mathematics, computer science, electrical engineering, industrial engineering and operations research, and statistics departments..

Only students already enrolled in one of these doctoral programs at Columbia are eligible to participate in this specialization. Students should fulfill the requirements below in addition to those of their respective department's Ph.D. program. Students should discuss this specialization option with their Ph.D. advisor and their department's director for graduate studies.

Applied Mathematics Doctoral Program

Computer Science Doctoral Program

Decision, Risk, and Operations (DRO) Program

Electrical Engineering Doctoral Program

Industrial Engineering and Operations Research Doctoral Program

Statistics Doctoral Program

The specialization consists of either five (5) courses from the lists below, or four (4) courses plus one (1) additional course approved by the curriculum committee. All courses must be taken for a letter grade and students must pass with a B+ or above. At least three (3) of the courses should come from outside the student’s home department. At least one (1) course has to come from each of the three (3) thematic areas listed below.

Specialization Requirements

• COMS 4231 Analysis of Algorithms I
• COMS 6232 Analysis of Algorithms II
• COMS 4111 Introduction to Databases
• COMS 4113 Distributed Systems Fundamentals
• EECS 6720 Bayesian Models for Machine Learning
• COMS 4771 Machine Learning
• COMS 4772 Advanced Machine Learning
• IEOR E6613 Optimization I
• IEOR E6614 Optimization II
• IEOR E6711 Stochastic Modeling I
• EEOR E6616 Convex Optimization
• STAT 6301 Probability Theory I
• STAT 6201 Theoretical Statistics I
• STAT 6101 Applied Statistics I
• STAT 6104 Computational Statistics
• STAT 5224 Bayesian Statistics
• STCS 6701 Foundations of Graphical Models (joint with Computer Science) 

Information Request Form

Ph.d. specialization committee.

• View All People
• Faculty of Arts and Sciences Professor of Statistics
• The Fu Foundation School of Engineering and Applied Science Professor of Computer Science

Richard A. Davis

• Faculty of Arts and Sciences Howard Levene Professor of Statistics

Vineet Goyal

• The Fu Foundation School of Engineering and Applied Science Associate Professor of Industrial Engineering and Operations Research

Garud N. Iyengar

• Data Science Institute Avanessians Director of the Data Science Institute
• The Fu Foundation School of Engineering and Applied Science Professor of Industrial Engineering and Operations Research

Gail Kaiser

Rocco a. servedio, clifford stein.

• The Fu Foundation School of Engineering and Applied Science Wai T. Chang Professor of Industrial Engineering and Operations Research and Professor of Computer Science

John Wright

• The Fu Foundation School of Engineering and Applied Science Associate Professor of Electrical Engineering
• Data Science Institute Associate Director for Research

• Department of Counseling, School and Educational Psychology >
• Academics >
• Doctoral Degrees >

Educational Data Science, PhD

VIRTUAL OPEN HOUSE Thursday, Nov. 9 Event Details Register Now

Our doctoral program in educational data science equips you with equity-focused, critical quantitative research methods, applicable in U.S. and global education contexts. You will gain exposure to critical methods that provide opportunities to learn cutting-edge methodologies that can make a difference in education and beyond.

Our program provides the foundation you need to study educational problems, influence policy, or shape the future as a faculty member—in higher education, K–12 school settings, or non-profit, governmental or educational research centers. Relying on educational big data, data mining or learning analytics will teach you to leverage big data and use critical quantitative methods harnessed for educational equity. We aim to develop you as future educational researchers and data analysts whose professional research training and positionality are deeply rooted in equity.

On this page:

Why educational psychology at ub.

The features of our program include:

• Educational big data and data mining: Use tools of data science to build data warehouses, extract data for specific research and education purposes, and model important educational outcomes and processes. Learn how to turn raw data into useful information through statistics, artificial intelligence, machine learning, data visualization and other tools.
• Equity-oriented, critical educational data science: Gain exposure to critical methods that provide opportunities to learn cutting-edge methodologies in educational data science that can make a difference in education and beyond.
• Learning analytics and experiential learning with hands-on real/big data analyses: Engage in measurement, collection, analysis and reporting of data about learners and their contexts, to help you understand and optimize learning and learning environments.
• STEM approved:  This program allows international students the opportunity to apply for the 24-month STEM OPT (Optional Practical Training) extension.

Program Overview

Career Opportunities

Graduates with a PhD in educational data science can pursue employment in the following areas:

• In academia and research, PhD graduates from an Educational Data Science program can work as faculty members specializing in educational data science, evaluation, and assessment. These roles focus on conducting research to drive educational innovation, improve learning outcomes, and apply technology in education. Faculty members analyze data to assess educational programs, evaluate student performance, and measure instructional effectiveness, contributing to data-informed decisions that shape policy and practice in the field.
• In K–12 and higher education institutions, they can work as data analysts or learning analytics specialists. These roles focus on using data to enhance student outcomes, optimize curriculum design, and support informed institutional decision-making.
• In the government and public policy sector, data science graduates can influence educational policy at local, state, or national levels. They can hold positions in policy development, program evaluation, or research analysis, using data to assess the effectiveness of educational programs and inform policy decisions.
• Nonprofit organizations and NGOs often seek data science graduates to support mission-driven initiatives aimed at improving educational equity and outcomes for underserved communities. These roles may involve educational research, program evaluation, and data management.
• Corporate training and development departments offer data science graduates opportunities to use data in optimizing employee training programs, professional development initiatives, and performance assessments. Graduates help organizations make data-driven decisions to enhance workforce development.

Program Coursework

Required courses (20 credits).

• CEP 500 Fundamentals of Educational Research
• CEP 510 Psychometric Theory in Education
• CEP 522 Statistical Methods I (4 credits)
• CEP 523 Statistical Methods II (4 credits)
• CEP 541 Human Growth and Development
• CEP 560 Psychology of Learning and Instruction

Distribution Requirements (27 credits)

Data analytics (choose two).

• CEP ### Foundations of Educational Data Science and Analytics (Currently, CEP 512)
• CEP ### Advanced Programming for Educational Data Analytics (Currently, CEP 533)

Measurement and Statistics (choose three)

• CEP 524 Experimental Design
• CEP 525 Applied Multivariate Analysis
• CEP 526 Structural Equation Modeling
• CEP 527 Analysis of Large-Scale Databases
• CEP 528 Hierarchical Linear Modeling
• CEP 529 Applied Regression Analysis
• CEP 530 Introduction to Meta-Analysis
• CEP 531 Applied Survival Analysis in Education and Social Sciences

Substantive Issues of Educational Policy and Practice (choose two)

• CEP 533 Topical Seminar
• ELP 566 Comparative and Global Studies in Education
• ELP 575 Education and Globalization
• ELP 585 Sociological Bases of Education
• ELP 592 American Education for International Students
• ELP 615 Critical Race Theory
• ELP 620 Educational Transitions P–20
• ELP 626 Policy Formulation and Analysis
• LAI 512 Readings in Multicultural Literature
• LAI 525 Science, Technology and Human Values
• LAI 529 Computers in Early and Primary Education

Qualitative Research Methods (choose two)

• ELP 593/594 Qualitative Research Methods Part I and Part II (2 semesters)
• LAI 515 Action Research to Improve Teaching and Learning
• LAI 625 Discourse Analysis Research
• LAI 669 Qualitative Techniques in Educational Research
• LAI 619 Qualitative Research Design (prerequisite: LAI 669)
• LAI 626 Advanced Qualitative Research in Field Methods (prerequisites: LAI 669 and 619; permission of advisor and IRB approval)
• NUS 697 Advanced Qualitative Methods

Qualifying Paper and Dissertation (15 credits)

• CEP 700 Individual Guidance Project (PhD Qualifying Paper; 3 credits)
• CEP 702 Individual Guidance Dissertation (12 credits)

Example Schedule

• CEP 522 Statistical Methods I
• Choose one data analytics course
• CEP 523 Statistical Methods II
• Choose one substantive issues course
• Choose two measurement and statistics courses (CEP 524–531)
• Choose one qualitative research methods course (e.g., ELP 593)
• Choose one substantive issues course (e.g., CEP 533)
• Choose one measurement and statistics course (CEP 524–531)
• Choose one qualitative research methods course (e.g., ELP 593 or LAI 669)
• CEP 700 Qualifying Paper 
• CEP 702 Dissertation

Recommended Electives

• CEP 594 Practicum in Teaching
• CEP 703 Independent Study
• ELP 589 Education and Socialization

Research Design, Measurement and Assessment, Statistics and Data Analysis

• CEP 502 Assessment of Learning and Instruction
• COM 636 Research Procedures in Communication
• LAI 638 Using Rasch Modeling to Develop Measurement Instruments
• NUS 695 Advanced Statistical Techniques
• NUS 706 Psycho-Social Measurement and Questionnaire Construction
• SOC 608 Social Statistics II: Causal Models (Advanced regression techniques)

Research and Assessment Courses in the Disciplines

• LAI 547 Assessing Mathematics
• LAI 569 Introduction to Research in Music Education
• LAI 623 Research Seminar in English Education
• LAI 637 Research in Science Education
• LAI 640 Seminar in Mathematics Education Research
• LAI 657/658 Analysis of Quantitative Research in Learning and Instruction
• LAI 686 Critical Interpretations of Research (multiple disciplines)

Program Handbook

Graduate assistantships.

UB Graduate School of Education tuition and fees are among the lowest and most competitive in the nation. We strive to provide funding opportunities for doctoral students, so students have as little debt as possible. Opportunities across campus may be found through the Career Design Center and the Graduate School Fellowships and Scholarships page.  There may be assistantships, fellowships, scholarships or university and external funding options. Some funding sources are competitive so you are encouraged to consult with program faculty. Compensation ranges from hourly pay only, to a stipend, to tuition remission plus a stipend. Generally, assistantships require 20 hours of work per week.

Program Faculty

Seong Won Han

Associate Professor Educational Leadership And Policy

431 Baldy Hall North Campus Buffalo, NY 14260

Phone: 716-645-1080

Email: [email protected]

Associate Professor Counseling, School And Educational Psychology

Associate Professor Learning And Instruction

423 Baldy Hall North Campus Buffalo, NY 14260

Phone: 716-645-1127

Email: [email protected]

Jaekyung Lee

Professor Counseling, School And Educational Psychology

Professor Educational Leadership And Policy

409 Baldy Hall North Campus Buffalo, NY 14260

Phone: 716-645-2484

Email: [email protected]

Michele E. Shanahan

Clinical Associate Professor Counseling, School And Educational Psychology

Phone: 716-645-1109

Email: [email protected]

Application Requirements

In an effort to make the application process more equitable, the GRE/MAT is no longer required for admissions consideration. If you still plan to take the GRE/MAT exam, you can send your scores through the testing agency, and they will automatically be added to your application; however, they are not required for admission consideration to this program.

You must have a baccalaureate degree from an accredited institution.

Submit your completed online application, which includes:

• Application fee:  A $50 non-refundable application fee, submitted electronically through UB's ePayment system.
• Contact information for at least three individuals  who will each be asked to provide an electronic recommendation letter.
• Unofficial transcripts  from all colleges attended. (UB transcripts are automatically submitted for current UB students and alumni.)
• Statement of interest: Statement of your career goals and objectives.

Former/Maiden Name : Please provide us with your former/maiden name if you have one. When requesting transcripts, please ask the sending institution to indicate your current name and former/maiden name.

Admission Decision:  The admission decision will be communicated to you as soon as review is complete. The decision is based on a number of factors and is the result of a thorough and deliberate process. All decisions are final and cannot be appealed.

In-State Residency Tuition

In order to qualify for the in-state residency tuition rate, you must provide residency documentation indicating you have lived in New York State (NYS) 12 months before your semester start date.

If accepted, you will need to upload three documents to qualify for the in-state tuition rate. See  Required Documents for Residency Application  for more information. 

International Applicant Additional Requirements

• Official original proof of your degree
• A copy of your passport biographical page
• TOEFL minimum score is 250 for computer-based test, 600 for paper-based test and 79 for internet-based test
• IELTS Academic Test minimum score is 6.5 overall
• PTE minimum score is 55 overall
• DET minimum score is 120 overall
• Financial documentation:   International graduate applicants must document their ability to pay for all costs incurred while studying in the U.S.
• An official bank statement

All financial forms and supporting documentation with required signatures must be uploaded with your application and dated within one year of your intended enrollment date.

Questions about the program?

Program Director

Associate Professor

--------------------- Department of Counseling, School and Educational Psychology 423 Baldy Hall

716-645-1127 [email protected]

We have a collection of frequently asked questions that may help you. If your questions are still unanswered, we are glad to help! Contact our admission office .

Questions About the Admission Process?

Office of Graduate Admission Graduate School of Education 366 Baldy Hall, North Campus 716-645-2110 [email protected]

MS Admissions FAQ

Eligibility, do i need to have a background in computer science, can i apply with a 3-year bachelor's degree, is there a minimum gpa for admission, are there minimum gre scores, what is the deadline for submitting an application, can i submit my application after the due date, i submitted my application before the due date, but have materials i would like to add. can i add materials to my application after the due date, application requirements, what materials are required for my application to be considered complete, how can i find out if my application is complete, what is the application fee, can the application fee be waived, is the gre required, is the toefl required for all international applicants, is it acceptable to send a photocopy of my test scores with my application, will my application be considered if any of the required materials are missing, who do i contact if i am having issues with the application system, cost and financial aid, how much does your program cost, how do i apply for scholarships, who is eligible for a scholarship, how much are scholarships, are there minimum requirements for maintaining a scholarship, how do i apply for need-based aid.

• Free Application for Federal Student Aid ( FAFSA )

Application Decision and Notification

When are admissions decisions made, when will i know if i received a scholarship, how can i check on the status of my application, what does it mean if my application has been wait-listed, if i have been added to the wait list, when will i find out if i am admitted or rejected, program details, will i receive a master of arts or a master of science upon graduation, can i change my degree to add or remove a specialization after i have already started, how long does the average student take to complete their degree, can i complete my degree in one year, do you offer an online program.

Request Info If you have any remaining questions, please feel free to email us at [email protected].