Students have the flexibility to pursue the Master of Science in Analytics degree on a part- or full-time schedule. Part-time students enroll in one or two courses each quarter and take their courses in the evenings or on Saturdays. Full-time students take three courses per quarter. Some of their courses may be offered during the day. All courses are taught at the NBC Tower in downtown Chicago.
Students earn the Master of Science in Analytics by successfully completing up to fourteen credit courses and a final capstone project. The Analytics curriculum consists of the following:
- Statistics Bootcamp (noncredit)
- 2 Foundational courses (1 credit, 1 noncredit)
- 9 Core courses
- 2 Electives
- 2 Capstone courses
Analytics Degree Time to Completion
Typically, full-time students can complete the Master of Science in Analytics program in one and a half years. Part-time students typically complete the program in two-three years. Students may apply to start in either the Spring or Autumn quarters.
|Time to Completion|
|Full-time Spring Start||1.25 years (5 quarters)|
|Full-time Autumn Start||1.5 years (6 quarters)|
Our program builds a basis in analytics theory that will be applied in advanced analytics classes that span several analytics disciplines and specialities.
This course provides general exposure to basic statistical concepts that are necessary for students to understand the content presented in more advanced courses in the program. Bootcamp begins one month prior to a student’s start quarter.
Foundation courses provide the basis for our rigorous analytics degree that will support the theoretical, strategic, and practical analytics studies in more advanced courses. Students with sufficient preparation may be eligible to bypass either of these courses.
Core courses allow students to build their theoretical analytics knowledge and practice applying this theory to examine business problems. The required Leadership Skills core course teaches how to make the ties between data analysis learnings and business objectives. Each of the nine core courses is required to earn the Master of Science in Analytics.
- MSCA 31001: Research Design for Business Applications
- MSCA 31003: Leadership Skills: Teams, Strategies, and Communications
- MSCA 31006: Time Series Analysis and Forecasting
- MSCA 31007: Statistical Analysis
- MSCA 31008: Data Mining Principles
- MSCA 31009: Machine Learning and Predictive Analytics
- MSCA 31010: Linear and Nonlinear Models for Business Applications
- MSCA 31012: Data Engineering Platforms for Analytics
- MSCA 31013: Big Data Platforms
Explore advanced analytics strategies and applications. Students are required to complete two electives. Our program continually adds electives to evolve with the analytics landscape. Alumni are able to take classes, when available, at reduced tuition.
- MSCA 32001: Financial Analytics
- MSCA 32003: Marketing Analytics
- MSCA 32004: Credit and Insurance Risk Analytics
- MSCA 32005: Real Time Analytics
- MSCA 32007: Data Visualization Techniques
- MSCA 32009: Health Analytics
- MSCA 32013: Optimization and Simulation Methods for Analytics
- MSCA 32014: Bayesian Methods
- MSCA 32015: Digital Marketing Analytics in Theory and Practice
- MSCA 32017: Advanced Machine Learning and Artificial Intelligence
- MSCA 32018: Natural Language Processing and Cognitive Computing
- MSCA 32019: Real Time Intelligent Systems
- MSCA 32020: Reinforcement Learning and Advanced Optimization
Linear Algebra and Matrix Analysis is available as an elective to students who were not required to take it as a Foundation Course.
The required capstone project is completed over three quarters. The capstone courses start with the core course, Research Design for Business Applications. Part-time students generally start their capstone project three to four quarters before their projected graduation. Full-time students start their capstone project in their third quarter.
Non-Credit Workshops and Short Courses
Short courses and workshops are offered to support student success in the relevant concurrent courses and electives.