Because the modern workplace has become more project-focused than ever, employers often hire contractors and expect them to be fully trained. This places the onus on us as educators to graduate students who can handle real-world issues. We're up to the task. Recognizing the significance of Big Data no longer is sufficient. Robinson's Master of Science in Analytics students learn how to truly understand Big Data by pinpointing underlying patterns, predicting the future, and harnessing that power to improve people's lives. Our graduates are ideal candidates for the range of data-driven jobs that have emerged across a variety of sectors such as data science, quantitative marketing analysis, credit risk analysis, predictive modeling, health informatics and web analytics. The M.S. in Analytics curriculum comprises 21 credit hours of required courses and nine credit hours of approved elective course work. The standard program is a three-semester, lock-step, cohorted offering. However, working professionals can complete the program on a part time basis, can extend the length of the program, and also take courses in the summer. Full time students also have the option of completing the program in 12 months by taking their electives in the summer.