Master of Science in Data Science

Nu’s master of science in data science focuses on 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, analytic programming, and artificial intelligence. 

The National Science Foundation (NSF) has awarded a $20 million grant to a partnership of prestigious universities led by University of California, San Diego, and including National University, Yale University, the Massachusetts Institute of Technology, the University of Pennsylvania, and the University of Texas at Austin. Working together, the universities will form The Institute for Learning-enabled Optimization at Scale (TILOS).

Our five-year research partnership will focus on the optimization of artificial intelligence (AI) and machine learning. We will work closely with industry leaders to develop optimization tools that will enable real-world improvements in key industries, including chip design, robotics, and communications networks. State-of-the-art analytical software will be used in all courses.

Learn how to blend business, computer science, and statistics to solve real-world problems.

• Machine learning. Neural networks. Artificial intelligence. What does it all mean, and where is it taking the field of data science? To address the spectrum of issues in data science and analytics, National University designed an industry-current curriculum that includes core courses in statistical topics as well as four specializations for advanced applications of data science and analytics in unique fields: Artificial Intelligence and Optimization, Business Science and Analytics, Database Science and Analytics, and Health Science and Analytics.

Program Requirements

• 15 courses; 67.5 quarter units

Core Requirements
7 courses; 31.5 quarter units

• ANA 600 Fundamentals of Analytics – 4.50
• ANA 605 Analytic Models & Data Systems – 4.50
• ANA 610 Data Management for Analytics – 4.50
• ANA 615 Data Mining Techniques – 4.50
• ANA 620 Continuous Data Methods, Appl – 4.50
• ANA 625 Categorical Data Methods, Appl – 4.50
• ANA 630 Advanced Analytic Applications – 4.50

Students must select one area of specialization.

Capstone Requirements

3 courses; 13.5 quarter units

Students must complete all core and area of specialization courses prior to starting the capstone course sequence.

• ANA 699A Analytic Capstone Project I – 4.50
• ANA 699B Analytic Capstone Project II – 4.50
• ANA 699C Analytics Capstone Project III – 4.50

Specializations

Specialization in Business Analytics Requirements
5 courses, 22.5 quarter units

• BAN 640 Performance MGT & SCM Process – 4.50
• BAN 645 Prediction in Marketing – 4.50
• BAN 650 Probabilistic Finance Models – 4.50
• BAN 655 Analytical Security & Ethics – 4.50
• ANA 505 AI & Optimization Topics – 4.50

Specialization in Database Analytics Requirements
5 courses, 22.5 quarter units

• ANA 650 Database Design for Analytics – 4.50
• ANA 655 Data Warehouse Design & Devel – 4.50
• ANA 660 Advanced SQL Programming – 4.50
• ANA 665 Data Mining & Machine Learning – 4.50
• ANA 505 AI & Optimization Topics – 4.50

Specialization in Health Analytics Requirements
5 courses, 22.5 quarter units

• HCA 626 Healthcare Information Systems – 4.50
• COH 606 Epidemiology – 4.50
• ANH 604 Clinical Research Analytics – 4.50
• ANH 607 Health Outcomes Research – 4.50
• ANA 505 AI & Optimization Topics – 4.50

Specialization in AI / Optimization
Students must complete a minimum of 22.5 quarter units for the AI/Optimization Specialization.

Total Specialization Requirements:
5 courses; 22.5 quarter units

• ANA 500 Python for Data Science – 4.50
• ANA 670 Applied Optimization Methods – 4.50
• ANA 675 Neural Network & Deep Learning – 4.50
• ANA 680 Machine Learning Deployment – 4.50
• ANA 505 AI & Optimization Topics – 4.50

Degree and Course Requirements

• To obtain National University’s Master of Science in Data Science, students must complete at least 63 graduate units. A total of 13.5 quarter units of graduate credit may be granted for equivalent graduate work completed at another regionally accredited institution, as it applies to this degree, and provided the units were not used in earning another advanced degree. Please refer to the graduate admissions requirements for specific information regarding application and evaluation.

Program Learning Outcomes
As a graduate of National University’s Master of Data Science program, you’ll understand how to:

• Integrate components of data science to produce knowledge-based solutions for real-world challenges using public and private data sources.
• 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 and implement 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.

Admissions

• Enrolling in a university is a big decision. That’s why our dedicated admissions team is here to guide you through the admissions process and help you find the right program for you and your career goals.
• To that end, we’ve simplified and streamlined our application process, so you can get enrolled in your program right away. Because we accept and review applications year round, you can begin class as soon as next month, depending on your program and location of choice.
• Learn more about undergraduate, graduate, military, and international student admissions, plus admissions information for transfer students. You can also learn more about our tuition rates and financial aid opportunities.

Why Choose National University

• Four-Week Courses
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