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. Using three methods of training to advance students skill sets.
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)
- Elective (4 units)
- ProSeminar (0 units)
- Management Science for Analytics (4 units)
- Customer and Social Analytics (4 units)
- Capstone Prep (2 units)
- Elective (8 units)
- ProSeminar (0 units)
- Capstone Project (4 units)
- Electives (8 units)
- ProSeminar (0 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
- Special Topics in Analytics
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:
- Ingram Micro
- Pacific Life
- Edwards Life Sciences
- Wells Fargo
- Molina Healthcare
- Blue Shield
- American Honda Motor Co.
- JD Power
- 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
- Kaiser Permanente – Small Business Group Analysis
- Pacific Life – Predicting policyholder lapse behavior
- Competitive Analytics – People analytics
- Wells Fargo – Build customer level models using advanced techniques to predict customer value, outcomes, and potential services
- Inscape – Predict Viewing Content of top 100 national networks
- Experian – Utilize credit attributes to predict consumer behavior
- Los Angeles Rams – Ticket Sales Lead Score Model
- Cerius Executives – Marketing engagement and conversion tool creation
- Ingram Micro – Customer intent and prediction mode
- Paciolan – Predicting the key drivers for live event attendance, lead score by product offering to drive revenue growth
- Disney – Advanced analytics for Walt Disney Parks & Resorts, U.S
- Niagara Bottling – Predictive analysis
- Amazon – Recommending Alexa skill categories based on skill attributes
- Edwards Lifesciences – Predicting quality and compliance trends for product lines
- Experian – Utilize credit attributes to predict customer performance
- Kaiser Permanente – Retention of customers in small-business groups
- Eaton – Aftermarket demand analysis
- LA / IBM – Determine
costs of benefits in HR contracts true
- Competitive Analytics – Competitive pricing for consumer industries
- DecisionReady – Predictive modeling and automation of claims processing
- Coca Cola – Demand forecasting model for restaurant traffic and sales
- Pacific Life – Statistical analysis of life expectancy
I chose the UCI MSBA program because of the broad range of course options. Besides studying marketing analytics, we had the opportunity to take elective courses such as natural language processing, which helped me with the ability to understand consumer attitudes and needs.Mia Zhang, MSBA '20