MS in Economics & Computer Science Plan of Study
Drexel’s LeBow College of Business provides you with plan of study options that work with your schedule. Whether you’re looking to attend the university full-time or you’re a working professional looking to take advantage of our part-time options, there’s a plan of study that works for you.
MS in Economics & Computer Science Part-time
Part-time graduate students in the economics and computer science program can finish in as little as three years, depending on the number of courses taken each term. Part-time students will determine a customized plan of study with their program advisor. See the current Drexel Course Catalog for complete course descriptions.
Total credits - 45 credits (semester equivalent: 30 credits)
Required courses – 30 credits
Required electives in computer science – 9 credits
Additional electives – 6 credits
MS in Economics & Computer Science Required Electives (9 credits)
Add depth to your skillset with electives that incorporate a deep exploration of the theories and methodologies required to excel in the ever-changing world of computer science.
Additional Electives (6 credits)
Additional electives may be taken at LeBow and throughout the university to complement and support career and educational goals. Consult your advisor for more information.
MS in Economics & Computer Science Part-time Plan of Study
| Term | Course | Title | Credits |
|---|---|---|---|
| Term 1 (6 credits) | CS 570* | Programming Foundations | 3 |
| ECON 540 | Introduction to Econometrics and Data Analysis | 3 | |
| Term 2 (6 credits) | CS 571* | Advanced Programming Techniques | 3 |
| ECON 550 | Econometrics | 3 | |
| Term 3 (6 credits) | CS 520* | Computer Science Foundations | 3 |
| ECON 560 | Time Series Econometrics | 3 | |
| Term 4 (6 credits) | CS Required Elective** | 3 | |
| ECON 548 | Mathematical Economics | 3 | |
| Term 5 (6 credits) | CS Required Elective** | 3 | |
| ECON 614 | Macroeconomics | 3 | |
| Term 6 (6 credits) | CS Required Elective** | 3 | |
| Elective | 3 | ||
| Term 7 (6 credits) | ECON 610 | Microeconomics | 3 |
| Elective | 3 | ||
| Term 8 (3 credits) | ECON 700 | Economics Seminar | 3 |
MS in Economics & Computer Science Full-time
Below is a sample plan of study for a student enrolled in our full-time Master of Science in Economics & Computer Science degree program. Full-time students will determine a customized plan of study with their program advisor. See the current Drexel Course Catalog for complete course descriptions.
Total credits – 45 credits (semester equivalent: 30 credits)
Required courses – 30 credits
Required electives in computer science – 9 credits
Additional electives – 6 credits
MS in Economics & Computer Science Required Electives (9 credits)
Add depth to your skillset with electives that incorporate a deep exploration of the theories and methodologies required to excel in the ever-changing world of computer science.
Additional Electives (6 credits)
Additional electives may be taken at LeBow and throughout the university to complement and support career and educational goals. Consult your advisor for more information.
MS in Economics & Computer Science Full-time Plan of Study
| Term | Course | Title | Credits |
|---|---|---|---|
| Term 1 (9 credits) | ECON 548 | Mathematical Economics | 3 |
| CS 570* | Programming Foundations | 3 | |
| ECON 540 | Intro to Econometrics and Data Analysis | 3 | |
| Term 2 (9 credits) | ECON 614 | Macroeconomics | 3 |
| CS 571* | Advanced Programming Techniques | 3 | |
| ECON 550 | Econometrics | 3 | |
| Term 3 (9 credits) | ECON 560 | Time Series Econometrics | 3 |
| CS 520* | Computer Science Foundations | 3 | |
| Elective | 3 | ||
| Term 4 (9 credits) | ECON 610 | Microeconomics | 3 |
| CS Required Elective** | 3 | ||
| CS Required Elective** | 3 | ||
| Term 5 (9 credits) | CS Required Elective** | 3 | |
| ECON 700 | Masters Seminar | 3 | |
| Elective | 3 |
*CS 570, CS 571, and CS 520 may be replaced with different CS Electives, per approval by the CS Department
CS Electives**
- CS 500 - Fundamentals of Databases
- CS 510 - Introduction to Artificial Intelligence
- CS 521 - Data Structures and Algorithms I
- CS 525 - Theory of Computation
- CS 575 - Software Design
- CS 590 - Privacy
- CS 610 - Advanced Artificial Intelligence
- CS 613 - Machine Learning