ODU's Graduate School to Launch Master of Science in Data Science and Analytics Program this Fall
July 01, 2020
Old Dominion University has received approval from the State Council for Higher Education for Virginia (SCHEV) to offer a new Master of Science in Data Science and Analytics, starting in the fall semester.
Under the auspices of the Graduate School, this interdisciplinary program merges faculty from the Departments of Computer Science, Mathematics and Statistics, Decision Sciences and Information Technology.
"This dynamic new program brings together faculty expertise across multiple departments, providing students with the cutting-edge skills necessary for success in data-driven work environments," said Robert Wojtowicz, vice provost and dean of the Graduate School.
This 30-credit-hour, non-thesis degree program includes a curriculum of 18 core credits (six courses), a choice of two concentrations and a capstone project. The concentrations are in Computational Data Analytics and Business Intelligence & Analytics. The core classes are designed to lay the foundation required by a data scientist working in any field. They will establish proficiency in data discovery, collection, processing and cleaning; exploratory data analysis using statistics and visual analytics; and statistical modeling for prediction/forecasting. The capstone project in both concentrations will provide the opportunity to synthesize knowledge from coursework to solve real-world problems.
Coursework for the Computational Data Analytics concentration focuses on programming languages, use of complex statistical tools and mathematical modeling. Graduates will be able to enter data science, analytical and statistical fields. Coursework for the Business Intelligence & Analytics concentration focuses on providing students with the skills to gather, analyze and use data to make informed decisions. Graduates will be prepared to enter business and organizations that need professionals to help make informed recommendations.
Application requirements include:
- A bachelor's degree from a regionally accredited institution or equivalent.
- Official transcripts from all institutions attended.
- A resumé.
- A statement of professional goals.
- Undergraduate coursework or experience in computer science, mathematics, statistics, information technology, engineering or a related field.
- Two letters of recommendation.