Data Analytics Graduate Major (MS)
This program is available at the following location:
The MS in Data Analytics Master’s degree, offered through the Department of Statistics, provides advanced training for those seeking expertise and skill in the management, manipulation and analysis of data to address real world problems. The MS in Data Analytics Master’s degree does not require an advanced mathematics background and will be attractive to currently employed professionals. This program will help employers meet workforce planning goals and contribute to self-improvement goals of current employees.
The MS in Data Analytics Master’s degree is a 45-credit distance, online curriculum via Ecampus although students in residence at OSU may also choose to work toward the degree. The required courses include programming in python and R, one and two sample statistical methods, regression analysis, multivariate and time series analysis, classification methods, ordination and machine learning. Elective courses cover a wide range of data analysis methods including time-to-failure data, methods for large and complex data, data visualization, sampling methods, and methods for genomics data.
The MS in Data Analytics degree is offered as a non-thesis program only. Students have an advisor and graduate committee to review their program of study, provide mentoring and advising and to assess the student via their capstone project and final oral exam.
For general information about the MS in Data Analytics program, email firstname.lastname@example.org
Major Code: 6160
Upon successful completion of the program, students will meet the following learning outcomes:
- Conduct research or produce some other form of creative work.
- Demonstrate mastery of subject material.
- Conduct scholarly or professional activities in an ethical manner.
- Gain a thorough understanding of the theoretical and applied principles of statistics.
- Demonstrate the ability to summarize a technical report and/or statistical analysis and interpret results. Also shows the ability for broader implication of application in the statistical field.
- Communicate statistical concepts clearly and professionally in oral form.
- Demonstrate preparedness to provide guidance in statistical design and analysis.
|ST 351||INTRODUCTION TO STATISTICAL METHODS||4|
|Mathematics to the level of calculus is recommended but not required|
|ST 516||FOUNDATIONS OF DATA ANALYTICS||4|
|ST 517||DATA ANALYTICS I||4|
|ST 518||DATA ANALYTICS II||4|
|ST 558||MULTIVARIATE ANALYTICS||3|
|ST 566||TIME SERIES ANALYTICS||3|
|ST 595||CAPSTONE PROJECT||3|
|Computer Science Core|
|CS 511||PROGRAMMING AND DATA STRUCTURES||4|
|CS 512||DATA SCIENCE TOOLS AND PROGRAMMING||4|
|CS 513||APPLIED MACHINE LEARNING||4|
|Select 12 credits from the following courses:||12|
|DESIGN AND ANALYSIS OF PLANNED EXPERIMENTS|
|APPLIED SURVIVAL ANALYSIS|
|R PROGRAMMING FOR DATA|
|MODERN STATISTICAL METHODS FOR LARGE AND COMPLEX DATA SETS|
|INTRODUCTION TO QUANTITATIVE GENOMICS|
|STATISTICAL METHODS FOR GENOMICS RESEARCH|
Major Code: 6160