Master of Science in Business Analytics | Academics

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The UCI Merage School MSBA curriculum is designed to provide you with a strong foundation in modern data science to solve critical business challenges. The STEM Certified (36-month Optional Practical Training) MSBA program differentiates itself by offering flexible curricular tracks and leverages three areas of training in Data Management, Analytics Methods, and Business Context to bring a strategic advantage to businesses across all industries. Taught by world-class faculty, students will learn to extract business value in the real-world application through our industry-partnered Capstone Project.

The one-year MSBA program consists of 13 courses – eight required core courses and five electives – for a minimum of 52 units. The curriculum uses three methods of training to advance students' skill sets:

MSBA Tracks

The degree incorporates flexible curricular tracks aligned with your career path in three business analytics contexts:

  • Data Analytics – actuaries, database administrators, financial analysts, information security analysts, management analysts, survey researchers
  • Marketing Analytics – market research analysts, marketing specialists, marketing managers, sales managers, survey researchers
  • Operations Analytics – analytics specialist, financial analysts, management analysts, operations research analysts, statisticians, transportation, storage and distribution managers

Within these flexible tracks, you may select electives across subject areas depending on your interests and career aspirations. 

A key component to the program is the capstone project where you engage with our industry partners to develop data-driven solutions for unique business challenges. Under the supervision of faculty and industry professionals, the capstone project provides you with the analytical tools and strategic insight to be a leader in the field.

Program Structure and Courses

  • Foundations of Business Analytics (2 units)
  • Statistics for Data Science (4 units)
  • ProSeminar (0)

  • Foundations of Marketing (4 units)
  • Data and Programming for Analytics (4 units)
  • Machine Learning for Analytics (4 units)
  • ProSeminar (0 units)

  • Management Science for Analytics (4 units)
  • Customer and Social Analytics (4 units)
  • Capstone Prep (2 units)
  • Electives (8 units)
  • ProSeminar (0 units)

  • Capstone Project (4 units)
  • Electives (12 units)
  • ProSeminar (0 units)

  • Foundations of Business Analytics (2 units)
  • Statistics for Data Science (4 units)
  • ProSeminar (0)

  • Foundations of Marketing (4 units)
  • Data and Programming for Analytics (4 units)
  • Machine Learning for Analytics (4 units)
  • ProSeminar (0 units)

  • Management Science for Analytics (4 units)
  • Customer and Social Analytics (4 units)
  • Capstone Prep (2 units)
  • Elective (4 units)
  • ProSeminar (0 units)

  • Capstone Project (4 units)
  • Electives (8 units)
  • ProSeminar (0 units)


  • Electives (8 units)

BANA 200 Foundations of Business Analytics
This course will provide an overview of business analytics and the theory and practice underpinnings of the MSBA curricular tracks in data analytics, marketing analytics, and operations analytics. The course will also provide the students a working knowledge of the R programming language, including a coverage of how R can be used for data visualization and graphics, data management, and basic statistics.

BANA 201A Statistics for Data Science
Methods of statistical inference, emphasizing applications to administrative and management decision problems. Topics: classical estimation and hypothesis testing, regression, correlation, analysis of variance, decision analysis, and forecasting.

BANA 201B Management Science for Analytics
An introduction to computer-based models for decision-making.  Topics include optimization (linear programming, integer programming, network flows, quadratic programming, goal programming), Monte Carlo simulation, decision analysis, and heuristics for non-convex optimization.  This course makes extensive use of optimization software, including Excel Solver and AMPL.

BANA 205 Foundations of Marketing
Introduction to the field of marketing. Objectives include developing familiarity with fundamental concepts, theories, and techniques in marketing, and acquainting students with the type of decisions made by marketing managers including customer targeting, product, pricing, distribution, promotion, and research.

BANA 211 ProSeminar
The ProSeminar courses are designed to hone career building skills, provide technology workshops and industry panel discussions, and generally prepare the students for a successful career in business analytics. During the Fall and Winter quarters, we will have guest speakers and panelists from various companies involved with business analytics, and in the Spring we focus on preparing for the CAP and aCAP certifications.

BANA 212 Data and Programming for Analytics
The objective of this course is to challenge and teach students how to handle data that come in a variety of forms and sizes. This course guides students through the whole data management process, from initial data acquisition to final data analysis. Topics include: Python programming, data visualization, web crawling, data manipulation and querying, and natural language processing.

BANA 273 Machine Learning for Analytics
Introduces methods to mine data repositories for business intelligence to facilitate analytical decision-making. Topics include clustering for market segmentation, association rules to discover relationships between different purchase decisions, Naive-Bayes classification techniques for decision making using decision-trees.

BANA 277 Customer and Social Analytics
Examines how to create value through web, mobile and social media analytics. Topics include: digital and social strategies; web analytics; search analytics; display and mobile advertising; social networks and social influence; social media and sentiment analysis; social media monetization; and crowdsourcing.

BANA 298A Business Analytics Capstone Prep
During the Winter quarter teams of up to four students will select the topic for their capstone project, conduct background research, and familiarize themselves with relevant data sets and software.

BANA 298B Business Analytics Capstone Project
During the Spring quarter students will do the bulk of their analysis on the capstone project, with two key deliverables due at the end of the quarter: (i) a presentation to MSBA faculty and students, and (ii) a final project report. Prerequisite: BANA 298A.

  • Natural Language Processing and Applications
  • Big Data & Cloud Computing
  • Marketing Analytics
  • Business Data Management
  • Advanced Machine Learning
  • Mastering Predictive Analytics
  • Supply Chain Analytics
  • Technologies & Analytics Consulting
  • Art & Science of Applied Forecast Modeling
  • Special Topics in Analytics

Capstone Project

The Master of Science in Business Analytics program seeks to enhance in-class learning with industry practice by providing students with the opportunity to work on real-life data science problems with industry partners. The 6-month capstone project allows students to work in teams  partnering with companies to derive business value from data analytics. Advised by faculty and staff members, students run their projects from start to finish, assessing needs and devising project-specific approaches to the work.

Our Capstone Partners have included Fortune 500 companies from across the industry sector, including social media companies, major league sports teams, leading consulting firms, financial institutions, entertainment conglomerates, and more.

Our globally recognized industry partners help our students develop and showcase their knowledge of business analytics, hone their communication skills, and dive deep into the field.

Capstone Sponsor Companies:

  • Disney
  • Experian
  • Ingram Micro
  • SAP
  • Kaiser
  • Pacific Life
  • Edwards Life Sciences
  • Los Angeles Rams
  • Paciolan
  • Wells Fargo
  • KPMG
  • Molina Healthcare
  • Octane
  • Blue Shield
  • Skyworks
  • American Honda Motor Co.
  • Anaheim Ducks
  • JD Power

  • Avanath Capital Management – Predict property performance in the real estate market
  • SAP – Evaluating effectiveness of software development programs
  • KPMG – Analyze healthcare claims data for DEI initiatives
  • Octane – Develop decision intelligence model for startup accelerator
  • - Leveraging Data and AI for mental health and well-being
  • Edwards Lifesciences – Derive business insights from audit intelligence program & Establish standardized procedures to streamline operations
  • Ingram Micro – Obtain insights and trends to help marketing, sales, and investments teams & Develop framework for forecasting product demand in particular regions
  • Big Brothers, Big Sisters – Assessing recruitment processes and criteria for volunteers
  • Blue Shield – Analyze patient claim data pertaining to hospital visits and medical procedures
  • Anaheim Ducks – Retention model for fans
  • OBAGI – Predicting churn and evaluating effectiveness of product portfolio

  • Los Angeles Rams – Developing business insights from long term fans
  • KPMG – Assess how individual behavior drives company carbon footprint
  • Edwards Lifesciences – Model customer service data to predict future complaints & Develop competitor analysis for upcoming products
  • Paciolan – Increase segmentation accuracy and ROI on ad expenditures
  • Ingram Micro – Modeling customer purchase behavior
  • Kaiser Permanente – Capturing workforce staff and employee effectiveness
  • BlueShield – Understanding the cost impacts of new surgical centers
  • Anaheim Ducks – Analysis of buyer trends and patterns
  • – Forecast corporate revenue growth for SMB companies
  • Guitar Center – Predicting customer churn and developing marketing strategy
  • Pacific Life – Forecast disbursements through analyzing financial data
  • PADI – Improve customer retention and evaluate loyalty program

  • Skyworks – Demand management and supply chain management
  • Experian – Understanding customer behavior from financial profiles
  • D. Power – Model automotive returning and leasing behavior
  • Edwards Lifesciences –Gain insights from analytics and model inventory levels
  • Kaiser Permanente – Analyzing effects of COVID-19
  • Paciolan – Marketing analysis campaigns
  • Blue Shield – Determine factors for annual checkups and screenings
  • Ingram Micro – Build product recommendation engine

  • Disney - Text Analytics to Predict Movie Performance
  • Experian - Predict Probability of Customer Bankruptcy and Customer Credit Default
  • Ingram Micro - Reseller Network Customer Value and Predictive Model to Forecast Churn Behavior of Customers
  • Kaiser Permanente Retention of Customers in Small-Business Groups
  • Pacific Life Distribution Partner Engagement Patterns
  • Edwards Lifesciences Develop Models to Increase Value of Corporate Quality Data Analysis & Develop Product Lifecycle Trending and Predictive Model Tools for Critical Care Quality
  • Paciolan Create a Scoring System Identifying Accounts for Renewal
  • Wells Fargo Develop Algorithms to Predict Customer Attrition, Service and Forecasting
  • KPMG Corporate Partner Tool Development 
  • Molina Healthcare Predictive Model Using Natural Language Processing to Identify Grievances
  • Blue Shield Analyze Medical Claim Data for Business Insights
  • Skyworks Customer Data Platform Development and Scoring Model
  • American Honda Motor Co. Develop Social Media Database and Analytics Platform
  • JD Power Predict U.S. Automotive Sales Performance 
My favorite class was Machine Learning because I felt that it provided me with the fundamental knowledge to understand many of the predictive models used in the industry today. The program faculty is well versed with the leading analytics technologies and are also engaged in their own cutting-edge research, often citing examples of their work in classroom lectures.