Business Analytics, BS
The Business Analytics joint concentration between the OID and STAT departments is designed to build deep competency in the skills needed to implement and oversee data-driven business decisions, including (i) collecting, managing, and describing datasets, (ii) forming inferences and predictions from data, and (iii) making optimal and robust decisions. Business analytics makes extensive use of statistical analysis, and the applications of business analytics span all functional areas.
Students choosing the Business Analytics concentration are ideally suited for the growing set of careers broadly defined under the header of “data science” with responsibilities for managing and analyzing data. In addition, the concentration provides an excellent complement to students who choose to focus on one of the functional areas of business (e.g., accounting, finance, marketing, operations).
For more information: https://oid.wharton.upenn.edu/programs/undergraduate/business-analytics-joint-concentration/
Business Analytics Concentration
| Code | Title | Course Units |
|---|---|---|
| Complete one course unit of Advanced Data Analysis competency | 1 | |
| Forensic Analytics | ||
| Applied Data Analysis | ||
| Applied Machine Learning 1 | ||
| Machine Learning 1 | ||
| Big Data Analytics | ||
| Computational Text Analysis for Communication Research | ||
| Foundations of Data Science | ||
| Financial Derivatives | ||
| Data Science for Finance | ||
| FinTech | ||
| Healthcare Data and Analytics | ||
| People Analytics | ||
| Data and Analysis for Marketing Decisions | ||
| Models for Marketing Strategy | ||
| Special Topics: Experiments for Business Decision Making | ||
| Special Topics - Marketing Analytics | ||
| Applied Probability Models in Marketing | ||
| Intro to Analytics and the Digital Economy | ||
| Introduction to Operations Management | ||
| Analytics and the Digital Economy | ||
| Artificial Intelligence, Business, and Society | ||
| Enabling Technologies | ||
| Databases for Analytics | ||
| Advanced Decision Systems: Evolutionary Computation | ||
| Computer Simulation Models | ||
| Decision Support Systems | ||
| Information Strategy and Economics | ||
| Introduction to Python for Data Science | ||
| Thinking with Models: Business Analytics for Energy and Sustainability | ||
| Statistical Computing with R | ||
| Predictive Analytics for Business | ||
| Applied Machine Learning in Business | ||
| Forecasting Methods for Management | ||
| Introduction to Bayesian Data Analysis | ||
| Data Analytics and Statistical Computing | ||
| Modern Data Mining | ||
| Modern Regression for the Social, Behavioral and Biological Sciences | ||
| Sample Survey Design | ||
| Introduction to Python for Data Science | ||
| Applied Econometrics I | ||
| Complete one course unit of Data Collection competency | 1 | |
| Forensic Analytics | ||
| Database and Information Systems | ||
| Big Data Analytics | ||
| Computational Text Analysis for Communication Research | ||
| Data Science for Finance | ||
| Healthcare Data and Analytics | ||
| People Analytics | ||
| Special Topics: Experiments for Business Decision Making | ||
| Special Topics - Marketing Analytics | ||
| Analytics in Excel VBA | ||
| Intro to Analytics and the Digital Economy | ||
| Analytics and the Digital Economy | ||
| Artificial Intelligence, Business, and Society | ||
| Business Computer Languages | ||
| Enabling Technologies | ||
| Databases for Analytics | ||
| Advanced Decision Systems: Evolutionary Computation | ||
| Computer Simulation Models | ||
| Information Strategy and Economics | ||
| Introduction to Python for Data Science | ||
| Thinking with Models: Business Analytics for Energy and Sustainability | ||
| Statistical Computing with R | ||
| Data Collection and Acquisition: Strategies and Platforms | ||
| Predictive Analytics for Business | ||
| Forecasting Methods for Management | ||
| Data Analytics and Statistical Computing | ||
| Modern Data Mining | ||
| Sample Survey Design | ||
| Introduction to Python for Data Science | ||
| Complete one course unit of Optimization competency | 1 | |
| Introduction to Optimization Theory | ||
| Investment Management | ||
| Financial Derivatives | ||
| Technology Management, Information and the Digital Economy | ||
| Introduction to Operations Management | ||
| Analytics for Service Operations | ||
| Scaling Operations in Technology Ventures: Linking Strategy and Execution | ||
| Analytics and the Digital Economy | ||
| Introduction to Management Science | ||
| Computer Simulation Models | ||
| Mathematical Modeling and its Application in Finance | ||
| Thinking with Models: Business Analytics for Energy and Sustainability | ||
| Forecasting Methods for Management | ||
| Complete one additional course unit from above BUAN electives or the equivalent from the following: | 1 | |
| Engineering Probability | ||
| Big Data, Big Responsibilities: The Law and Ethics of Business Analytics | ||
| Advanced Decision Systems: Evolutionary Computation | ||
| Operations Strategy Practicum | ||
| Probability | ||
| Stochastic Processes | ||
| Other Wharton Requirements | 33 | |
| Total Course Units | 37 | |
- 1
Students can count only one of the two courses (CIS 4190/5190 or CIS 5200) towards the Business Analytics concentration.
Other Wharton Requirements
| Code | Title | Course Units |
|---|---|---|
| First-Year Foundations | ||
| BEPP 1000 | Introductory Economics for Business Students 1 | 1 |
| MATH 1400 | Calculus, Part I | 1 |
| or MATH 1100 | Calculus for Wharton Students | |
| Writing | ||
| Critical Writing Seminar | 1 | |
| Business | ||
| Business Breadth (non-concentration courses) | 3 | |
| Leadership Journey | ||
| WH 1010 | Business and You | 0.5 |
| WH 2010 | Business Communication for Impact | 0.5 |
| MGMT 3010 | Teamwork and Interpersonal Influence | 0.5 |
| Capstone Course/Project | 0.5 | |
| Fundamentals | ||
| ACCT 1010 | Accounting and Financial Reporting | 1 |
| ACCT 1020 | Strategic Cost Analysis | 1 |
| BEPP 2500 | Managerial Economics | 1 |
| FNCE 1000 | Corporate Finance | 1 |
| FNCE 1010 | Monetary Economics and the Global Economy | 1 |
| LGST 1000 | Ethics and Social Responsibility | 1 |
| or LGST 1010 | Law and Social Values | |
| MKTG 1010 | Introduction to Marketing | 1 |
| OIDD 1010 | An Introduction to Operations, Information and Decisions | 1 |
| STAT 1010 | Introductory Business Statistics | 1 |
| STAT 1020 | Introductory Business Statistics | 1 |
| Global Economy, Business & Society | ||
| One course unit required | 1 | |
| Technology, Innovation & Analytics | ||
| One course unit required | 1 | |
| Liberal Arts & Sciences | ||
| Foreign Language | 1 | |
| Second semester-level course or equivalent required | 1 | |
| Humanities | ||
| At least one course unit required | 1 | |
| Natural Science, Math & Engineering | ||
| At least one course unit required | 1 | |
| Social Science | ||
| At least one course unit required | 1 | |
Cross-Cultural Perspectives | ||
| Three course units required 2 | 3 | |
| Unrestricted Electives | ||
| Five course units required | 5 | |
| Total Course Units | 33 | |
- 1
For students who take ECON 0100 Introduction to Micro Economics and ECON 0200 Introductory Economics: Macro in place of BEPP 1000 Introductory Economics for Business Students of these courses can be slotted for BEPP 1000 on the worksheet. The second course may be used to fulfill a General Education Distribution or Unrestricted Elective requirement.
- 2
Two can double-count as Humanities; Natural Science, Math & Engineering; Social Science; or Flex Gen Ed.
The degree and major requirements displayed are intended as a guide for students entering in the Fall of 2023 and later. Students should consult with their academic program regarding final certifications and requirements for graduation.