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 twelve credit courses and a final capstone project. The Analytics curriculum consists of the following:
|New MScA Curriculum Requirements||Current MScA Curriculum Requirements|
|Available to students entering autumn or spring quarter of the Academic Year 2020-21||Available only to students entering autumn 2020 or prior terms|
|12 required 100-Unit Courses:
7 Core Courses:
|13 Courses 100-Unit Courses:
9 Core Courses:
|MSCA 31006: Time Series Analysis and Forecasting||MSCA 31006: Time Series Analysis and Forecasting|
|MSCA 31007: Statistical Analysis||MSCA 31007: Statistical Analysis|
|MSCA 31008: Data Mining Principles||MSCA 31008: Data Mining Principles|
|MSCA 31009: Machine Learning and Predictive Analytics||MSCA 31009: Machine Learning and Predictive Analytics|
|MSCA 31010: Linear and Nonlinear Models for Business Applications||MSCA 31010: Linear and Nonlinear Models for Business Applications|
|MSCA 31012: Data Engineering Platforms for Analytics or MSCA 31013: Big Data Platforms||MSCA 31012: Data Engineering Platforms for Analytics|
|MSCA 31003: Leadership Skills: Teams, Strategies, and Communications or MSCA 31015: Data Science for Consulting||MSCA 31003: Leadership Skills: Teams, Strategies, and Communications or MSCA 31015: Data Science for Consulting|
|MSCA 31001: Research Design for Business Applications|
|MSCA 31013: Big Data Platforms|
|2 Capstone Courses|
|MSCA 34002: Capstone I, Research Design and Implementation||MSCA 34000: Capstone Project Implementation|
|MSCA 34003: Capstone II, Implementation and Writing||MSCA 34001: Capstone Project Writing|
|Any 3 elective courses||Any 2 elective courses|
|2 required 5-week, non-credit workshops (Introduction to Statistical Concepts and Advanced Linear Algebra for Machine Learning)||2 required 5-week, non-credit workshops (Introduction to Statistical Concepts and Advanced Linear Algebra for Machine Learning)|
|1 required 10-week, non-credit workshop (Python for Analytics)||1 required 10-week, non-credit workshop (Python for Analytics)|
|Full-time students: May be completed in 4 quarters or 5 with a summer internship||Full-time students: May be completed in 5 quarters or 6 with a summer internship|
|Part-time students: 2-3 years||Part-time students: 2-3 years|
Our program builds a basis in analytics theory that will be applied in advanced analytics classes that span several analytics disciplines and specialities.
Foundational non-credit 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 the programming course.
Pre-quarter foundational courses
First quarter foundational non-credit course
Core courses allow students to build their theoretical analytics knowledge and practice applying this theory to examine business problems. Each of the seven core courses is required to earn the Master of Science in Analytics. (Autumn 2020 students selecting the thirteen course curriculum take nine core courses.)
Additional core courses for students enrolled in the 13-course curriculum
Explore advanced analytics strategies and applications. Students in the 12-course curriculum are required to complete three elective courses while students enrolling in the 13- course curriculum take two electives.) Our program continually adds electives to evolve with the analytics landscape. Alumni are able to take classes, when available, at reduced tuition.
The required capstone project is completed over two quarters (for the 12-course curriculum) or three quarters (for the 13-course curriculum) and covers research design, implementation, and writing.
Students will generally start their capstone project two quarters before their projected graduation. Full-time students start their capstone project in their third quarter.
Non-credit short courses and workshops are offered to support student success in the relevant concurrent courses and electives.
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