2027 Notre Dame Online MS in Data Science vs. Washington Online MSIM Data Science Track: Cost, Curriculum, Admissions, and Format

The central distinction is the degree awarded, not whether either program can teach useful data science skills. Notre Dame's degree is an MS in Data Science. UW's is an MS in Information Management, with Data Science describing a track within that degree. The table separates that verified credential distinction from curriculum questions that require a current program plan.

A degree title can help communicate your focus to an employer, but it does not establish technical depth. If you want to develop and evaluate models, compare the required statistics, programming, and machine-learning work in each program. If you want to lead decisions about how organizations collect, govern, and use information, examine UW's broader MSIM requirements alongside its track courses.

Both options are presented as online programs, but online does not necessarily mean entirely asynchronous or travel-free. A program can include scheduled live sessions, team meetings, in-person activities, or a project with fixed meeting times. Those distinctions matter more to a working student than the word "online" alone.

Ask each program for the current schedule covering required live sessions, time zones, any campus visits, and the courses available in your intended term. UW applicants should also obtain written confirmation that the Data Science track - not merely the MSIM degree - is available through their specific online pathway. If travel or live attendance would prevent you from enrolling, resolve that question before paying an application fee.

A defensible side-by-side price requires current, program-specific figures for both schools. Without confirmed tuition schedules and degree requirements for the relevant 2026 intake, neither an exact total nor a claim that one program is cheaper would be reliable. Tuition can change by academic year, and a quoted per-credit price may exclude fees.

Request an itemized estimate from each school using the credits required in your pathway. Compare tuition and mandatory fees first, then add any materials, technology, required travel, and financing costs that apply to you. Subtract only aid or employer reimbursement you have confirmed you can receive. If affordability is the deciding factor, compare the final estimates with budget-friendly data science master's degrees rather than assuming either named program is the lowest-cost route.

A common mistake is treating tuition as the entire investment. For a working applicant, a schedule that requires reduced hours or unpaid time off can change the decision even if its billed price is lower.

Notre Dame's degree designation makes data science the program's stated field; UW places its Data Science track inside an information-management degree. Neither label, by itself, tells you how many courses cover statistical inference, machine learning, data engineering, or organizational decision-making. Use the current degree audit or course plan to compare required work, available electives, and the final project on the same basis.

For a technical data scientist role, look for substantive programming, statistics, model evaluation, and opportunities to work with imperfect real-world data. For analytics leadership or information-strategy roles, assess how students learn to frame stakeholder questions, manage information responsibly, and communicate results. If building reliable data pipelines is a priority, check whether that work appears in required courses or only as an elective; a comparison of AI master's curricula that include data engineering illustrates why that distinction matters.

Ask to see recent capstone descriptions or project expectations. A course title mentioning AI or machine learning is less persuasive than evidence that students implement methods, assess their limitations, and explain results to an intended audience.

Do not assume the two schools use identical prerequisites or that every UW online MSIM pathway has the same application process. Before applying, check each program's current admissions page for degree eligibility, application materials, deadlines, test policies, and any mathematics, statistics, programming, or work-experience expectations. Confirm whether a requirement is mandatory or whether it is recommended preparation.

Applicants without a computer science degree should focus on demonstrating the skills relevant to their target curriculum, rather than assuming their major settles the question. Coursework, professional projects, and a clear account of your quantitative work may help explain your readiness, but they do not automatically satisfy a formal prerequisite. The distinction is also useful when considering studying AI at graduate level without a CS degree. Ask admissions staff to evaluate any prerequisite uncertainty against your actual transcript before you invest in extra courses.

A single completion-time figure can mislead if it assumes a particular course load. The relevant comparison is each program's required credits and course sequence at the pace you can sustain, including when track electives or project courses are offered. Current, comparable completion schedules for the two intended online pathways should be confirmed with the programs rather than inferred from advertised timelines.

Ask each adviser to map a term-by-term plan for your preferred start date and weekly availability, then identify any courses offered only in specific terms. That exercise reveals whether a missed course would delay graduation. For context on how pacing changes the comparison, see these online data science master's duration comparisons; use each school's own plan for your final decision.

Both pathways could support applications to analytics and data-focused jobs, depending on a graduate's prior experience and demonstrated skills. Notre Dame's MS in Data Science may be easier to describe when applying for roles explicitly named data scientist. UW's MSIM may be especially relevant when a role combines analytics with information strategy, governance, product decisions, or organizational implementation. Those are fit judgments, not placement claims.

Work backward from several real job descriptions you would consider. Compare their required programming, statistical methods, data systems, and stakeholder responsibilities with each program's required courses and project opportunities. If a role demands production machine learning or substantial software engineering, do not assume that either degree title alone supplies that experience; ask how students can build and demonstrate it.

The U.S. Bureau of Labor Statistics reports a $120,230 median annual wage for data scientists in May 2025. That is an occupation-wide figure, not a starting salary or an outcome reported for either university. Your likely pay depends on your previous experience, role, employer, location, and the work you can demonstrate after graduation.

BLS also projects strong growth in data scientist employment over 2025-2035, but demand does not guarantee an individual graduate a job. When comparing potential returns, use salaries for the roles and industries you would realistically pursue; these sector-by-sector data science earnings comparisons can provide context. Avoid calculating a personal return by treating the national median as a salary increase caused by either degree.

Notre Dame and the University of Washington are institutionally accredited universities: Notre Dame by the Higher Learning Commission and UW by the Northwest Commission on Colleges and Universities. Institutional accreditation is not the same as a claim that either specific degree or track holds separate data science accreditation. Check the current institutional listings with the accreditors if accreditation affects employer reimbursement or other eligibility.

Professional recognition is a different question. Employers may value the institutions, but they will also assess the credential awarded, relevant coursework, experience, and projects. In particular, UW applicants should be comfortable explaining why an MSIM Data Science track matches the jobs they want, rather than assuming employers will read "MSIM" as an MS in Data Science.

Choose Notre Dame if a degree explicitly titled MS in Data Science aligns with your target roles and its confirmed courses, schedule, and total cost meet your needs. Consider UW if you want to connect data science with information-management practice and can confirm that the Data Science track's online course options support your goals. Neither is a universal winner: the better choice is the one whose required work builds the skills you lack without imposing an unworkable schedule or cost.

Before accepting an offer, obtain four items from each school: the current degree requirements, a personalized completion plan, written clarification of live or campus obligations, and an itemized cost estimate. For UW, add confirmation of online Data Science track availability. If an essential answer remains unclear, wait for clarification rather than choosing on reputation, a program title, or an unverified price comparison.

• Partnering with Students to Develop a Capstone for a... - PMC https://pmc.ncbi.nlm.nih.gov/articles/PMC11732519/
• What's the Difference Between Asynchronous and Synchronous Learning? | Ohio State Online https://online.osu.edu/content-hub/blogs/whats-the-difference-between-asynchronous-and-synchronous-learning/
• Online Learning | fitnyc.edu https://www.fitnyc.edu/academics/online-learning/index.php
• How to Become a Data Scientist | Harvard SEAS https://seas.harvard.edu/news/how-become-data-scientist
• Synchronous vs. Asynchronous Remote Instruction | UMBC https://calt.umbc.edu/teaching/synchronous-vs-asynchronous-remote-instruction/
• Prerequisite Key Topics - UVA School of Data Science https://datascience.virginia.edu/pages/prerequisite-key-topics