Credits required
45 or 18 Oregon State University is on a quarter-term system. There are four quarters each year and classes are 11 weeks long. This program's 45 or 18 quarter credits are equal to 30 or 12 semester credits.*
Cost per credit
$560 Cost per credit is calculated using tuition per credit for the current academic year. It does not include associated fees, course materials, textbook expenses, and other expenses related to courses.
Delivery
Online You can complete all or nearly all requirements of these programs online. View the master's curriculum or the certificate curriculum.
Start term
Fall

Data Analytics – Master of Science or Graduate Certificate

FAQ

Here are some of the most frequently asked questions about Oregon State's data analytics graduate programs.

1. How many applications do you receive and how many applicants do you admit each year?

We receive about 100 applications per year. How many students we admit depends on the availability of our faculty. We admitted about 30 new students to our 2019 and 2020 cohorts.

2. Is funding available?

At this time, university-sponsored funding in the form of fellowships or assistantships is not available for the data analytics programs.

3. Tell me more about the master’s program vs. the graduate certificate. What can you do with the M.S. that you cannot with the certificate?

The certificate program is an 18-credit program that covers the basics of statistical analysis and computer programming. The M.S. in Data Analytics program is a 45-credit graduate degree that includes the certificate content plus additional content on additional advanced and specialized statistical methods. Please see the documentation about our curriculum to learn about the specific courses.

4. Apart from the prerequisite class, are there any additional skills I am expected to know going into the program (e.g., certain level of mathematics, programming, statistics, etc.)?

Our prerequisite course includes training in basic statistics and an introduction to programming in statistical software. In addition to these skills, we expect incoming students to have basic computational skills at the level of college algebra.

5. What programming languages will be covered throughout the program? Is any prior knowledge of these languages needed?

Our courses include content on Python, SAS, C+ and R. There may be additional languages that are included in courses in the future. No prior knowledge in Python, SAS or C+ is needed. A basic introduction to R is assumed (see the program’s prerequisites). If you feel you need a refresher in R, there are many no-cost online tutorials.

6. Is there a recommended workload per quarter for working professionals?

This is a highly personal decision that depends on your situation. Oregon State requires all M.S. in Data Analytics students to be enrolled for a minimum of 3 credits each term, which is generally one class. Some students, for whom data analytics is a new subject or who have other commitments in their lives, choose to take one or two courses per term. Others take three classes per term.

7. What are graduates doing with their degrees?

A large proportion of our graduates will remain employed by their current employers; they are using this program to transition to a new position with their current employer. Other graduates have sought employment in various health care-related professions, the marketing sector and in technology-related industries.

8. Are there any internship opportunities throughout the program?

At this time, the data analytics master's program does not include internship experiences for credit.

9. What are my prospects for finding employment with a degree but no other background or experience in the field?

Data science and data analytics are used in almost every conceivable field. While some employers may prefer that applicants have knowledge of their field, our courses are conceived and taught so the material can be applied to any specialized field. After finishing our certificate or M.S. programs, you will be equipped to apply your newly learned skills to any field.

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