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

The central distinction is the credential's organizing subject. Syracuse offers a master's in applied data science through its School of Information Studies. UW offers an MSIM through its Information School, with Data Science as a track. Both can be relevant to analytics work, but a track within an information-management degree should not be treated as interchangeable with a degree expressly titled Applied Data Science.

This table compares what each option emphasizes without assuming that a degree title proves the depth of any particular technical skill.

A prospective data scientist should compare required courses and available electives, not simply favor the Syracuse title. Someone interested in managing data, information systems, and organizational decisions may find UW's broader framing useful. Neither conclusion substitutes for checking the current course plan.

Evaluate the curricula by what you must study and what you can elect to study. For Syracuse, inspect the applied data science core, the available advanced courses, and how students demonstrate their work. For UW, inspect both the MSIM core and the Data Science track: a course listed somewhere in the university catalog may not be offered online or count toward the track when you need it.

For either program, look beyond labels such as "machine learning" or "analytics." Check course descriptions and recent syllabi for statistical reasoning, programming, data preparation, model evaluation, responsible use of data, and substantial projects. If your goal is an AI-focused role but you need prerequisite preparation first, compare programs offering foundations for an AI master's rather than assuming either degree supplies a formal bridge.

A useful comparison is the work you could show an employer at graduation. Ask each program whether online students can complete an individual or team project using realistic data, what technical methods it permits, and whether the resulting work can be shared in a portfolio.

A reliable current, like-for-like total for these two programs cannot be established here. It would be misleading to compare one school's per-credit tuition with the other's estimated program total or to name a cheaper program without accounting for required credits and fees. Request a written cost estimate for your intended start term from each school.

For each estimate, distinguish tuition from mandatory university or online fees, then add any required materials and technology costs. Ask whether tuition can change during enrollment and whether a slower schedule changes the fees you pay. Employer tuition assistance and scholarships may reduce your personal cost, while borrowing can increase it.

If affordability is the controlling factor, compare the complete estimates before accepting an offer. Lower-cost artificial intelligence degrees online may be worth examining as alternatives, but their curricula and credentials should be compared against the job you actually want - not against sticker price alone.

Both are graduate programs, so applicants should consult each program's current online admissions page for its degree eligibility rules, application materials, deadlines, and any test policy. Specific current requirements - including whether a particular programming or mathematics course is mandatory - should not be assumed from the program names.

Even when a subject is not a formal prerequisite, evidence of readiness matters. An applicant can use transcripts, work projects, or a portfolio to show quantitative reasoning, programming, and experience explaining results. Before paying an application fee, ask admissions whether your prior coursework meets any stated requirements and whether professional experience can address a preparation gap. Self-study may help you succeed without formally satisfying a required course.

Neither program has one completion time that applies to every student. The time you need depends on required credits, course sequencing, how many courses you take at once, and when needed courses are offered. A published fastest-possible timeline is less useful to a working applicant than a term-by-term plan based on a sustainable workload.

Ask each school to map its current requirements to your preferred pace, including any final project or track-course sequencing. If finishing quickly is more important than choosing between these two credentials, compare shorter online data science master's programs as a separate option. Avoid assuming that "online" means you can accelerate at will.

Both options are offered online, but that description alone does not establish whether every class is self-paced or whether students must attend live sessions. The meaningful format comparison is operational: scheduled meeting times, time-zone fit, group-project expectations, assessment windows, and access to the courses required for the degree or track.

Request a sample schedule from each program for your first term and a later term containing advanced coursework. Someone with rotating shifts may need recordings and flexible deadlines; someone who learns best through discussion may prefer regular live interaction. Confirm any travel expectations directly rather than assuming that an online degree requires none - or that campus visits are part of it.

Both programs may support applications for data analyst, analytics, or data science work when graduates can demonstrate the skills an employer requests. Syracuse's degree title directly signals applied data science. UW's MSIM may also appeal to applicants interested in roles connecting analytics with information systems and organizational decisions. These are interpretations of program fit, not placement claims.

For a specific vacancy, compare its requirements with courses you can actually take and projects you can actually complete. A candidate targeting data pipelines or production systems should verify substantial engineering coursework rather than assume that any data science track covers it.

Data engineering preparation through an AI master's provides another comparison point if that skill set is central to your goal. Prior experience and a convincing portfolio will still matter alongside either credential.

Syracuse University is institutionally accredited by the Middle States Commission on Higher Education; the University of Washington is institutionally accredited by the Northwest Commission on Colleges and Universities. Institutional accreditation applies to the university. It should not be confused with a separate, program-specific endorsement of either data science curriculum or a guarantee of career outcomes.

Before enrolling, confirm each institution's current status with its accreditor and ask the program about any authorization restrictions relevant to where you will study. This is especially important if you live outside the institution's state; an online delivery format alone does not settle every enrollment question.

The U.S. Bureau of Labor Statistics reports a $120,230 median annual wage for data scientists in May 2025. That is an occupational figure across workers at different career stages - not an expected starting salary, a reported outcome for either program, or evidence that a master's degree caused an earnings increase.

Use salary information to assess plausible roles, then compare compensation for those roles against the full cost of attendance and any income you would forgo while studying. Location, industry, prior experience, and responsibilities can substantially change the comparison; data science salary opportunities across sectors can help frame that research.

Ask each school for recent, clearly defined graduate outcomes if available, including who was surveyed and whether figures describe salaries or salary changes.

Choose Syracuse for closer investigation if you want your credential and course plan centered on applied data science. Choose UW for closer investigation if you want to study data science within the wider discipline of information management. Neither is a universal winner: the better choice is the one whose confirmed courses, schedule, and net cost fit your intended work.

Before deciding, obtain the current degree audit and online course rotation from both programs. Identify the courses that address your target job's requirements, request comparable written cost estimates, and check a realistic term-by-term schedule. The most avoidable mistake is deciding from a degree title, a headline tuition rate, or an occupational salary figure without verifying what you will study and pay.

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