National University

Are you ready to develop problem-solving skills and get hands-on experience with data and analytics? Solving real-world challenges through statistical methods is the core of the Master of Science in Data Analytics program at National University. Three specializations are available to choose from — business analytics, database analytics, and health analytics — all of which cover specific nuances related to their areas of expertise.

To address the spectrum of issues in data analytics, this curriculum has been designed to include core courses in statistical topics as well as areas for advanced applications of data analytics in unique fields. Advanced topics include how to develop, implement, and maintain the hardware and software tools needed to make efficient and effective use of big data, including databases, data marts, data warehouses, machine learning, and analytic programming. State-of-the-art analytical software will be used in all courses.

The MS in Data Science program is designed for adult learners and can be completed in as few as 14 months with four-week classes. Faculty is made up of trained experts in the field who can offer career-focused knowledge and practical skills for analysis and data structures. Previous academic studies or industrial experience in such areas as math, statistics, computer programming, engineering, or science are helpful prerequisites for this master’s program. This degree is appropriate for both experienced professionals and recent college graduates.

Program Learning Outcomes

As a graduate of National University’s MS in Data Science program, students will be able to:

• Integrate components of data analytics to produce knowledge-based solutions for real-world challenges using public and private data sources
• Turn information into actionable knowledge through a three-month capstone project partnership with esteemed partner organizations and businesses
• Access opportunities for professional certifications on SAAS, Oracle, and Data Warehouses
• Evaluate data management methods and technologies used to improve integrated use of data
• Construct data files using advanced statistical and data programming techniques to solve practical problems in data analytics
• Design an analytic strategy to frame a potential issue and solution relevant to the community and stakeholders
• Develop team skills to ethically research, develop, and evaluate analytic solutions to improve organizational performance
• Design data marts
• Analyze complex database queries for real-world analytical application platforms
• Design medium-to-large data warehouses
• Evaluate machine learning methods and strategies for advanced data mining