The MS degree in business analytics focuses on the exciting and fast-growing field of "big data." Merging developments in marketing and customer analytics with operations research, business analytics, aspects of computer science and statistical methods, the specialization offers a technical, quantitative and statistically intensive program designed to train specialists in turning "big data" into business decisions. Analytics may be used as input for human decisions or may drive fully automated decisions about why some data pattern is observed, what will happen next and how a firm can adapt to optimize that outcome. Students have an option to customize their curriculum by specializing in decision science, healthcare analytics, marketing analytics or research analytics.
This 10-month program includes extensive coursework and an application of materials, preparing students for a range of job opportunities. In addition to the academic coursework, four enrichment seminars in topics ranging from teamwork and leadership to ethics and corporate social responsibility support our commitment to developing the "whole student" by incorporating professional development into the academic experience.
Distance Education Option via Online+
Students may enroll in the MS Business Analytics (BUAN) or MS Supply Chain Management (SCMN) degree program through distance education (online) and complete the degree requirements established for each MS program. Distance education offers regularly scheduled on-campus graduate courses to remote off-campus (distance) students using advanced virtual and video-conferencing technology. Distance students participate both synchronously (at a scheduled delivery time) and asynchronously (no scheduled delivery time). Instructors, courses, assignments, projects, exams and evaluations are identical for on-campus and off-campus students. Online+ courses are term-based (i.e., follow the regular academic schedule) and structured to maximize student engagement with faculty and other online+ students to support student success and degree completion.
Designed for working professionals, the online option allows students to enroll part-time and follows the same curriculum as the on-campus degree option. Please see degree requirements and plan(s) of study specific to Business Analytics or Supply Chain Management. Based on circumstance and timeline to completion, students enroll in one or two courses each semester, completing the degree in two years.
For more information, connect with the individual graduate program directly.
Requirements
Required Courses and Credits
| Code | Title | Credit Hours |
|---|---|---|
| Core Courses | ||
| MSBC 5070 | Programming Fundamentals for Analytics | 3 |
| MSBX 5415 | Data Analytics with AI | 3 |
| MBAX 6418 | Building Business Solutions with Generative AI and LLMs | 3 |
| MSBX 5405 | Structured Data Modeling and Analysis | 3 |
| MSBC 5180 | Machine Learning in Python | 3 |
| MSBX 5420 | Unstructured and Distributed Data Modeling and Analysis | 3 |
| MSBC 5190 | Modern Artificial Intelligence: Introduction to AI for Business | 3 |
| MSBC 5490 | BUAN Experiential Projects | 3 |
| Electives | ||
| Students will enroll in three of the following electives. | 9 | |
| Marketing Analytics Track | ||
| Market Intelligence | ||
| Customer Analytics | ||
| Digital Advertising | ||
| Decision Science Track | ||
| Optimization Modeling | ||
| Process Analytics | ||
| Supply Chain and Operations Analytics | ||
| Healthcare Analytics Track | ||
| Natural Language Processing for Healthcare Analytics | ||
| Concurrent Placeholder - Graduate ((track electives offered by School of Nursing)) | ||
| General Electives | ||
| Fundamentals of AI for Business | ||
| Agentic AI | ||
| Total Credit Hours | 33 | |
Experiential Projects
The experiential project pairs students with clients in industry to work on important practical problems in business analytics. Students work under the supervision of faculty and meet together weekly to discuss progress, jointly work on problems and to share experiences. This hands-on analytics project management experience prepares graduates to make an immediate meaningful contribution in the workplace.
For additional information, please visit Leeds School Graduate Programs or email us at leedsgrad@colorado.edu.
Tracks
The MS in Business Analytics offers tracks to develop analytic skills in specific disciplines: healthcare analytics, decision science and marketing analytics. Beginning Fall 2025, marketing analytics is offered as a standalone MS degree. Learn more below and on the Plan(s) of Study tab.
Decision Science Track
| Code | Title | Credit Hours |
|---|---|---|
| Decision Science Track Electives | ||
| MSBC 5680 | Optimization Modeling | 3 |
| MBAX 6410 | Process Analytics | 3 |
| MBAX 6843 | Supply Chain and Operations Analytics | 3 |
Healthcare Analytics Track
| Code | Title | Credit Hours |
|---|---|---|
| Healthcare Analytics Track Electives | ||
| NURS 6286 | Foundations of Healthcare Informatics (Fall) | 3 |
| NURS 6290 | Information Systems Life Cycle (Spring) | 3 |
| MSBX 5425 | Natural Language Processing for Healthcare Analytics | 3 |
Marketing Analytics Track
Plans of Study
The sample one-year plan of study found below is restricted to students who are not working professionals. Students who are working professionals enrolled in the online+ degree will engage a two-year plan of study. For more information, contact the department.
| Year One | ||
|---|---|---|
| Summer Review | Credit Hours | |
| (Summer B) | ||
| MSBC 5070 | Programming Fundamentals for Analytics | 3 |
| MSBX 5415 | Data Analytics with AI | 3 |
| Credit Hours | 6 | |
| Fall Semester | ||
| MSBX 5405 | Structured Data Modeling and Analysis | 3 |
| MSBC 5180 | Machine Learning in Python | 3 |
| MBAX 6418 | Building Business Solutions with Generative AI and LLMs | 3 |
| Two electives | 6 | |
| Credit Hours | 15 | |
| Spring Semester | ||
| MSBC 5190 | Modern Artificial Intelligence: Introduction to AI for Business | 3 |
| MSBX 5420 | Unstructured and Distributed Data Modeling and Analysis | 3 |
| MSBC 5490 | BUAN Experiential Projects | 3 |
| One elective | 3 | |
| Credit Hours | 12 | |
| Total Credit Hours | 33 | |
Decision Science Track
| Year One | ||
|---|---|---|
| Fall Semester | Credit Hours | |
| MSBC 5680 | Optimization Modeling | 3 |
| MBAX 6410 | Process Analytics | 3 |
| Credit Hours | 6 | |
| Spring Semester | ||
| MBAX 6843 | Supply Chain and Operations Analytics | 3 |
| Credit Hours | 3 | |
| Total Credit Hours | 9 | |
Healthcare Analytics Track
| Year One | ||
|---|---|---|
| Fall Semester | Credit Hours | |
| NURS 6286 Foundation of Healthcare Informatics | 3 | |
| MSBX 5425 | Natural Language Processing for Healthcare Analytics | 3 |
| Credit Hours | 6 | |
| Spring Semester | ||
| NURS 6290 Information Systems Life Cycle | 3 | |
| Credit Hours | 3 | |
| Total Credit Hours | 9 | |
Learning Outcomes
By the completion of the program, students will be able to:
- Analyze a business problem and develop feasible recommendations supported by evidence and data.
- Identify the key considerations for executives when defining and executing a business analytics strategy.
- Explain the principles and techniques of data management, exploration and visualization for business decision making.
- Recognize technology's social implications and build fair, ethical analytical solutions.
- Present data-driven insights clearly and effectively to stakeholders, ensuring professional communication of complex analytics.
- Interpret predictive modeling techniques, including regression, classification and time series analysis.
- Demonstrate proficiency in analytics tools like Python, R and SQL, leveraging advanced platforms and cloud-based solutions to write, debug code, manipulate data and build models for solving real-world business challenges.