Curriculum: Data Analytics – Master of Science

In Oregon State University's online Master of Science in Data Analytics, you will explore real data problems that are interesting and challenging as you equip yourself with the quantitative tools needed to gather, analyze and interpret data on a massive scale.

All courses in this program were developed and are taught by full-time Oregon State faculty members, and the course work integrates OSU's strengths in statistics, computer science, mathematics, policy and applied sciences such as genomics.

M.S. in Data Analytics (45 credits)

The 45-credit Master of Science in Data Analytics program consists of six core courses in statistics (21 credits); three core courses in computer science (12 credits); and four elective courses in statistics (12 credits). There is also a graduate option in health analytics.

Statistics core courses

  • ST 516 – Foundations of Data Analytics (4 credits)
  • ST 517 – Data Analytics (4 credits)
  • ST 518 – Data Analytics II (4 credits)
  • ST 566 – Time Series Analytics (3 credits)
  • ST 558 – Multivariate Analytics (3 credits)
  • ST 595 – Capstone Project (3 credits)

Computer science core courses

  • CS 511 – Programming Concepts for Non-majors (4 credits)
  • CS 512 – Big Data Management (4 credits)
  • CS 513 – Applied Machine Learning (4 credits)

Statistics elective courses

  • ST 525 – Applied Survival Analysis (3 credits)
  • ST 591 – Introduction to Quantitative Genomics (3 credits)
  • ST 592 – Statistical Methods for Genomic Research (3 credits)
  • ST 515 – Design and Analysis of Planned Experiments (3 credits)
  • ST 539 – Survey Methods (3 credits)
  • ST 537 – Data Visualization (3 credits)
  • ST 538 – Modern Analytical Methods for Large and Complex Datasets (3 credits)
  • ST 588 – Data Mining (3 credits)

Health analytics option

The option in health analytics consists of 12 credits. Three of the four elective courses in statistics must be ST 525, ST 591 and ST 592.

Prerequisites

To be admitted to either of these data analytics programs, you must have successfully completed an undergraduate statistics course at the level of ST 351 or equivalent. You must also have an understanding of study design, probability distributions, and the fundamentals of confidence intervals and hypothesis tests.

The OSU Transfer Course Search tool allows you to look up previous course work in order to find out if your class has been identified as an OSU course equivalent. Ecampus Enrollment Services can also help you navigate this tool to find any information that exists for ST 351.

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