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Data analytics is a fast-growing field and often the key to business strategy and the solution to complex questions. Data analysts are sought after in nearly every field. In fact, in a recent study IBM predicts that by 2020 demand for data professionals will increase by 364,000 job openings to 2,720,000.
The interdisciplinary Master of Science in Data Analytics is guided by an advisory board of professionals in the field, who help ensure the program provides rigorous courses in the analytical skills that are sought after across the arts, humanities, and sciences as well as within the business community.
The program is offered on both a full-time or part-time schedule for working professionals who are looking to build expertise in the field of data analytics. Most students complete the program in two years, but it can be completed in one year with the accelerated study.
Upon completion of the program, you will be able to demonstrate the following areas of knowledge:
- Define and solve complex data-based problems using appropriate statistical methodologies analyses.
- Select appropriate statistical and predictive methodologies with both sparse and large data sets.
- Provide appropriate theoretical interpretation of these results based on discipline-related concepts.
- Demonstrate written oral communications skills for conclusions drawn from the analyses of data.
- Create visual representations to increase understanding and utilization of complex data.
- Maintain collaborative team relationships to effectively contribute to a shared project.
- Have functional programming skills in the data-related language.
This interdisciplinary master’s program is designed to serve students in a broad range of fields. As a student in the program, you’ll tailor your course selection based on your individual interests and professional goals.
The structure of the curriculum includes five components:
Conceptual Foundations of Information and Data: 1 course
The required introductory course will provide you with a strong foundation on the general topic of data analytics
Analytic and Statistical Foundations: 4 courses
This section is a deep dive into techniques in analytic methods.
- Statistical Analysis – 2 courses
- Modeling Techniques – 2 courses
Professional Competencies: 2 courses
This component allows you to develop key competencies demanded by employers in a rapidly growing field. You’ll learn how to communicate and present effectively through courses ranging from business writing and data visualization to coding.
Disciplinary Competencies: 2 courses
Choose from a series of discipline-related electives that will allow you to narrow your focus and apply the skills you’ve learned to your area of interest.
Capstone: 1 course
You’ll culminate the program by completing an experimental capstone project that will incorporate and demonstrate the skills and knowledge you’ve gained.
- Application fee
- Personal statement
- Official GRE or GMAT required
- Official TOEFL or IELTS, if applicable
- Three letters of recommendation
- An undergraduate course in Calculus
- An undergraduate course in Statistics
- An introductory course in programming or basic knowledge of a programming language
Program taught in: