Economic Modeling, AI, and Data Science, MS
Overview
for the Master of Science in Economic Modeling, AI, and Data Science
The Economic Modeling, AI, and Data Science, MS degree (EMAIDS) combines a strong foundation in economics and data science with a discovery-based learning experience.
Students in the EMAIDS program gain a solid grounding in core economic concepts and analytical frameworks, integrated with practical applications in data science and artificial intelligence. Graduates will develop the theoretical knowledge and quantitative skills needed to uncover complex economic relationships, manage and analyze large datasets, and apply AI-enhanced methods for forecasting, classification, and pattern recognition. They will be prepared to deliver evidence-based policy recommendations and strategic solutions across diverse sectors, including business and finance, government, healthcare, and environmental organizations.
Admissions:
The Economic Modeling, AI and Data Science, MS degree program will accept applications starting from August 1st and continuing until April 1st the following year. Candidates must submit a transcript, three letters of reference, a statement of purpose and proof of English proficiency should their country of origin not have English as its home language. The GRE score is also required. Admission decisions are made on a rolling basis, starting in January and ending in April.
Degree Requirements
for the Master of Science in Economic Modeling, AI, and Data Science
| Code | Title | Hours |
|---|---|---|
| Required Coursework | ||
| ECON 500 | Microeconomics | 4 |
| ECON 506 | Programming for Economic Data Analytics | 4 |
| ECON 507 | Data Analytics for Applied Economics | 4 |
| ECON 508 | Econometrics for Data Science | 4 |
| Electives (choose 2): | 8 | |
| Applied Machine Learning in Economics | ||
| Causal Inference and Policy Evaluation | ||
| AI and Econometrics | ||
| One additional 500-level Elective Course in consultation with Program Director | 4 | |
| Capstone Course | ||
| ECON 509 | Capstone Project in Economics and Data Science | 4 |
| Total Hours | 32 | |
| Code | Title | Hours |
|---|---|---|
| Additional Requirements | ||
| Minimum GPA: | 3.0 | |
| Continuous enrollment is required; students not registered for a given semester must apply for a leave of absence. | ||
| The minimum length of stay in the Program is one year (fall and spring semesters plus one summer session). | ||
Learning Outcomes
for the Master of Science in Economic Modeling, AI, and Data Science
- Analytical and Computational Problem-Solving: Students will formulate, analyze, and solve complex economic problems using mathematical modeling, programming, simulation, advanced data science, and AI-driven techniques. They will identify appropriate tools, define assumptions, and test hypotheses using both theoretical and empirical methods.
- Data Proficiency, AI, and Quantitative Reasoning: Students will acquire, clean, manage, and analyze large and complex datasets. They will apply modern statistical, econometric, machine learning, and artificial intelligence methods to extract insights, evaluate policies, and make predictions—emphasizing reproducibility, transparency, and interpretation of uncertainty.
- Integrated Use of Technology, AI Tools, and Programming: Students will demonstrate proficiency in programming languages (e.g., Python, R, Julia, or Stata) and data visualization tools, incorporating AI-based workflows where appropriate, to automate processes, perform simulations, build models, and communicate findings effectively to both technical and non-technical audiences.
- Critical Thinking and Model Evaluation: Students will critically assess economic models, empirical strategies, and AI/ML algorithms—evaluating underlying assumptions, trade-offs, robustness, and relevance to real-world policy and business challenges. They will compare competing models and identify limitations in their application.
- Interdisciplinary and Ethical Awareness: Students will recognize the interplay between economics, AI, data science, and adjacent disciplines—such as computer science, finance, and public policy—when tackling complex societal and economic problems. They will consider ethical implications of data use, AI-driven decision-making, and policy design.
- Communication, Collaboration, and Leadership: Students will effectively communicate quantitative analyses and AI-enhanced insights through written reports, oral presentations, and visualizations. They will develop teamwork and leadership skills, preparing them to work across disciplines and engage diverse audiences.
- Professional Readiness and Application: Students will apply their skills in professional contexts—through capstone projects, internships, or real-world case studies—demonstrating their ability to address AI- and data-intensive economic problems in industry, government, or international organizations.
Contact Information
for the Master of Science in Economic Modeling, AI, and Data Science
Economics Department
Head of the Department: George Deltas
Associate Head: Seung-Hyun Hong
Economics Department website
214 David Kinley Hall, 1407 W. Gregory Dr., Urbana, IL 61801
(217) 333-0120, fax: (217) 244-6571
econ@illinois.edu
College of Liberal Arts & Sciences
College of Liberal Arts & Sciences website