Also known as: Computational Economics, Quantitative Economics and Computer Science, Data Science for Economics, Business Analytics and Computer Science
This program empowers you to understand and shape the digital economy by merging rigorous economic theory with advanced computer science principles. You will learn to analyze complex economic data, design computational models, and develop software solutions for challenges in markets, finance, and policy. The curriculum focuses on equipping you with both the analytical frameworks to interpret economic phenomena and the technical skills to build innovative data-driven applications.
Social SciencesQuantitative AnalysisData ScienceTechITBusinessSoftware DevelopmentMarket Research
A Week as a Student
Your Monday kicks off with a Programming Fundamentals I lecture, where you tackle object-oriented concepts in Python. Later, you meet your "Econometrics of Digital Markets" project group to brainstorm initial data scraping approaches for your market analysis. You realize you overlooked a key detail in the pre-lecture reading, requiring a quick review. After class, you ask the professor a clarifying question about Python syntax, getting immediate feedback. In the evening, you hit the campus gym for a quick workout before diving into readings for tomorrow's Microeconomics.
High School Preparation
Required Subjects
Pre-Calculus or CalculusStatisticsComputer Science (e.g., AP Computer Science A)PhysicsEnglish
Recommended GPA
3.7+
Advanced Courses (AP/IB/Honors)
AP Calculus BC
AP Computer Science A
AP Statistics
AP Microeconomics
AP Macroeconomics
Honors Linear Algebra
Recommended Activities
Coding Club/Hackathons
Economics Debate Club
Data Science Competitions
Investment Club
Math Team/Olympiad
Tutoring in Math or Computer Science
Application Essay Topics
Discuss how a specific technological advancement has reshaped an economic market or industry.
Propose a computational approach to solve a pressing economic challenge in your community or globally.
Explore the ethical implications of using AI and big data in financial decision-making or economic policy.
How do you envision the future interaction between economic theory and computational methods in addressing societal issues?
Alternative Path
While a direct bachelor's entry is common, you could start with an Associate's degree in Computer Science or Business Administration at a community college and then transfer to a four-year institution. Specialized coding bootcamps or data analytics certifications can provide foundational technical skills, but generally won't substitute for the comprehensive theoretical and quantitative education offered by a bachelor's program.
Core Subjects
Click on "i" to learn more about each subject
Career Prospects
Growing Study Prospects
Graduates of this program are highly sought after in diverse roles that require both analytical and technical prowess. You could become a Data Scientist, applying statistical and computational methods to large datasets; a Quantitative Analyst (Quant) in finance, developing trading algorithms and risk models; a Software Engineer specializing in FinTech or economic modeling platforms; an Economic Consultant, using data-driven insights to advise businesses and governments; or a Business Intelligence Developer, building systems to track and interpret market trends.
Impact of AI on this Study
Artificial intelligence profoundly impacts this field by offering powerful tools for economic analysis and prediction. You will learn to apply AI and machine learning techniques for tasks such as forecasting economic indicators, modeling complex market behaviors, developing algorithmic trading strategies, and processing vast amounts of unstructured data (like news articles or social media) to gauge market sentiment. Understanding these AI applications is crucial for building the next generation of economic and financial systems.