Master of Science in Data Science

Data Science is an interdisciplinary field that utilizes processes and systems to facilitate the precise analysis of massive amounts of information. Data scientists use this analysis to provide businesses and organizations with critical insights that shape decisions and solve problems. They are highly valued team members in major industries, including technology, finance, healthcare, management consulting, marketing, science, government policy and education. Join the renowned Notre Dame network and launch your data science career with a graduate degree that prepares you for success.

Program Details

Locations

Online with exclusive immersions at Notre Dame & Silicon Valley

Duration
21 months at half-time pace
Class Format
Small Evening Classes Online

Next Admissions Window

Starts October 2017

In collaboration with

With a shared vision and common goals, Notre Dame is proud to collaborate with AT&T around the MS-ACMS: Data Science program. Ensuring our curriculum aligns with industry means graduates enter the workforce with the latest skills for today’s job market and the ability to adapt to future requirements in the data science field.

Real-world projects and cases from industry & practical applications
Live immersion weekends with data science industry experts & thought leaders

The Notre Dame Edge

Notre Dame has a history of pioneering new research and inventions. The aerodynamics of glider flight, the transmission of wireless messages and the formula for synthetic rubber were all pioneered at our University. Therefore, it was a natural fit to develop an academically rigorous master’s degree program for an emerging field with immense growth potential–data science.

The application of data science is at the forefront of modern research, impacting science, government, business, healthcare and more. In keeping with our standards of excellence and innovation, the online Master of Science in Applied and Computational Mathematics and Statistics: Data Science Specialization program from Notre Dame gives students the edge they need to perform at the highest levels in this field.

Admissions

Notre Dame’s MS-ACMS: Data Science program does not require an undergraduate degree in a quantitative or technical field, making it accessible to professionals from every background. Applicants may use our free Data Science Readiness Assessment to evaluate their preparedness for the degree.

In addition to admissions requirements, the curriculum overview, tuition, logistics and other details are included in our prospectus brochure.

Online Degree for Working Professionals

Our MS-ACMS: Data Science program offers the flexibility of online learning classes shaped by real world applications, programs, and projects. Small classes with leading faculty and interactive online and in-person groups are combined to provide a student-centered learning approach.

Real World Data

Courses & skills informed by industry

Personal Attention

Small classes with Notre Dame faculty

Online Flexibility

Courses designed to fit your schedule

Weekend Immersions

Exclusive in-person events with experts & thought leaders

Curriculum

How can data analytics help heal a cancer patient, optimize network performance, drive business decisions, or improve learning?

What are the ethical frameworks we need in a data-driven world?

Can we predict financial events, weather patterns, disease transmission, or human behavior?

How can we communicate with and about data with clarity and precision?

Courses and Topics

  • Probability and Statistics
  • Data Mining, Databases, and Visualization
  • Behavioral Data Science
  • Statistical Learning
  • Communication and Storytelling
  • Ethics and Policies
  • Linear Models and Time Series
  • Data Science Process and Practice
  • Industry Case Studies
Find out if your skills are a match for the program. Take our Data Science Assessment!

Faculty

Steven Buechler Which breast cancer patients can safely avoid chemotherapy? Advances in biomedical technology have uncovered massive amounts of data about an individual’s cancer. Identifying predictive patterns in this data can inform treatment decisions. In his research, Professor Steve Buechler has analyzed the genomic data from a patient’s tumor to identify those likely to remain cancer-free following surgery. Learn More... Nitesh Chawla Can Big Data be used for the common good? Can we leverage data science to solve society’s grandest challenges? Professor Nitesh Chawla’s believes so, and is leading a research program in machine learning, data science, big data, and network science, where technology meets society. He also drives interdisciplinary innovations in health and wellbeing, learning analytics, climate and environmental sciences, and national security. Learn More... Alison Cheng How can Data Science ensure standardized tests are useful, valid and fair? Professor Ying (Alison) Cheng is a psychologist whose research focuses on quantitative methods in educational and psychological measurement research, particularly item response theory (IRT) and cognitive diagnostic modeling. Her research seeks to improve the precision, validity, fairness, and usefulness of large-scale standardized tests such as the GRE and statewide student assessments. Learn More... Jennifer Cronin How do you tell an unforgettable story with numbers? While data analysis continues to rank as one of the hottest skill categories for new recruits, companies still lack talent who can translate complex computational analysis into actionable insights. To meet this need, Professor Jennifer Cronin, an expert in interpersonal and organizational communication, studies how to effectively couple narrative storytelling with data to achieve better business decision-making. Learn More... Patrick Flynn How well do biometrics work (should we believe the hype)? How pervasive should the use of biometrics become, given that they are not error free? Biometric identification conjures images of both the best and the worst of human and government behavior—the identity information that would ensure that the ER workers have the proper blood type for you at the hospital could also be used to steal your money. Professor Patrick J. Flynn has been researching the feasibility of image-based biometrics and multi-biometrics since 2001. Learn More... Alan Huebner How can rigorous statistical training solve real world problems? By drawing on industry experience, Professor Alan Huebner, an Assistant Professional Specialist, has established himself as a leading researcher in the fields of computerized adaptive testing, sequential mastery testing, and diagnostic classification modeling. Learn More... Huy Huynh How can data science inform better investment decisions? To make sense of massive and complex financial data sets, companies are increasingly turning to data scientists for answers. In his research, Professor Huy Huynh focuses on capturing and analyzing new sources of financial data, building predictive models and running simulation study of market events. Learn More... Jun Li What’s happening inside a cancer tumor/tissue? Among the twenty thousand genes in the human genome, which ones are drivers of cancer and which can be targets of cancer treatment? Data mining can provide answers. Professor Jun Li’s research is devoted to answering these questions by mining data generated from a high-throughput technique called next-generation sequencing. Learn More... Scott Maxwell Can statistics offer an entirely different way of seeing the world? For Professor Scott Maxwell, statistics does just that. A quantitative psychologist, Professor Maxwell’s research interests are in the areas of experimental design and analysis and behavioral statistics. He is especially interested in the role of statistical power in achieving valid and replicable results. Learn More... Scott Nestler How should ethical considerations impact the use of data and analytics? A Certified Analytics Professional (CAP) and Accredited Professional Statistician (PStat), Professor Scott Nestler joined Mendoza College of Business in 2015 as an Associate Teaching Professor. Drawing on his experiences in academia, the military, and industry, Professor Nestler’s research focuses on ethical considerations related to the use of data and analytics. Learn More...
Dr. Roger Woodard announced as inaugural program director. Read more.

Program Endorsements

“AT&T is proud to collaborate with Notre Dame on this innovative online degree to train the next generation of data scientists”
— John Donovan
Chief Strategy Officer and Group President, Technology & Operations, AT&T
“Shaped by Notre Dame's mission to be a force for good in the world, our program launches skilled graduates into the data science careers of the future.”
— Mary Galvin
Warren Foundation Dean of the College of Science, University of Notre Dame

Join the Notre Dame Family!

Notre Dame’s passionate and committed alumni network is one of the most influential in the world. Our alumni are found in the highest leadership roles across all industries, including government, medicine, healthcare, finance, education and philanthropy. As a graduate student of the data science program, you will enjoy all of the benefits and opportunities of the renowned Notre Dame alumni network.

The application deadline for the August 2017 class has passed. We’re currently not accepting new applications.

We’ll soon be accepting applications for our 2018 class. If you’d like to stay informed on the latest admissions deadlines and events, join our mailing list.