Program Overview

Master's in Business Analytics Curriculum

The one-year MS Business Analytics degree focuses on the exciting and fast-growing field of big data. Designed to teach students how to translate data into strategic business decisions, our coursework integrates customer analytics with operations research, business analytics, computer science, and statistical methods. Students may customize their course selection by specializing in decision science or healthcare analytics. This technical, quantitative, and statistically intensive curriculum prepares students to excel in the field of business analytics.

Gain three critical skills by graduation:

1. How to capture and analyze complex structured and unstructured data sets.
2. How to develop your intuition about where business value can be found and articulate it to leadership.
3. How to deliver quantitative analysis in a format that C-suite executives can understand and use.

Curriculum Overview

Summer B Term - 6 credits

• MSBC 5070 Programming Fundamentals for Analytics: Designed as an introduction to Business Analytics, which considers the extensive use of data, methods, and fact-based management to support and improve decision making.
• MSBX 5415 Data Analytics with AI: Learn how to use AI as a tool for learning, doing stats, and unlocking data insights in this course.

Fall Term - 12 credits

• MSBX 5405 Structured Data Modeling & Analysis: This course will use platforms like Google Big Query, Tableau, and Snowflake to learn entity relationship diagrams, relational schema mapping, SQL, normalization, data visualization, and privacy/security.
• MSBC 5180 Machine Learning in Python: This course introduces predictive analytics, supervised and unsupervised segmentation, discriminant functions, overfitting, and evaluating and improving time series in machine learning.
• MBAX 6418 Building Business Solutions with Gen AI & LLMs: Use AI-assisted coding methods while learning language chains, flow design, multimodal LLMs, reasoning, efficient tuning, and tools for model deployment using team-based projects.

Fall Term Track-Specific Electives

• Decision Science Track Elective: MSBC 5680 Optimization Modeling
• Healthcare Analytics Track Elective: NURS 6286 Foundations of Healthcare Informatics
• Marketing Analytics Track Elective: MBAX 6331 Market Intelligence
• Artificial Intelligence Elective: MSBX 5417 Fundamentals of AI for Business

Spring Term - 15 credits

• MSBC 5490 Experiential Projects: Provides an opportunity to execute a project for a company, integrating coursework knowledge in an applied capstone experience.
• MSBX 5420 Unstructured Distributed Data Modeling & Analysis: Moves the student beyond structured data and sources into business scenarios where data is semi-structured to unstructured.
• MSBC 5190 Modern Artificial Intelligence: Learn an overview of Generative AI and LLMs used for deep learning and reinforcement learning and how to interpret and explain AI, while diving into the ethical components of AI.

Spring Term Track-Specific Electives

• Decision Science Track Electives:
  • MBAX 6843 Supply Chain & Operations Analytics
  • MBAX 6410 Process Analytics
• Healthcare Analytics Track Electives:
  • NURS 6290 Information Systems Lifecycle
  • MSBC 5425 NLP for Healthcare Analytics
• Marketing Analytics Track Electives:
  • MSBX 5310 Customer Analytics
  • MSBX 5320 Digital Advertising
• Artificial Intelligence Electives:
  • MSBX 5419 Agentic AI
  • MBAX 6420 IT & Business Strategy

Leeds School of Business

Boulder

995 Regent Drive
Koelbel Building
419 UCB
Boulder, CO
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