Economics and Data Science BS
Major: Economics and Data Science
Degree Awarded: Bachelor of Science (BS)
Calendar Type: Quarter
Minimum Required Credits: 180.0
Co-op Options: Three Co-op (Five years); One Co-op (Four years)
Classification of Instructional Programs (CIP) code: 30.3901
Standard Occupational Classification (SOC) code: 15-2041, 15-2051, 19-3011, 11-9199
About the Program
The STEM-designated Economics and Data Science is an interdisciplinary major that prepares students to work in an economy that has been transformed by the emergence of digital commerce and massive amounts of data. Coursework in data science teaches students how to manage, manipulate, and parse data to extract knowledge and insight.
Through the study of economics, students learn how the design of platforms shapes incentives, drives behavior, and determines social and economic outcomes including equity and efficiency. Students also learn how data may be used for predictive or causal analysis to inform business decisions or public policy.
The program provides excellent training for careers in the digital economy, including areas such as insurance, consulting, finance, retailing, and government. It also provides outstanding preparation for graduate study in business, data science, public health, economics, or other social sciences.
Additional Information
For more information please contact our LeBow College Undergraduate Advising department at lebowadv@drexel.edu or the College of Computing & Informatics at cciinfo@drexel.edu
Degree Requirements
| University Requirements | ||
| UNIV B101 | The Drexel Experience | 1.0 |
| or UNIV CI101 | The Drexel Experience | |
| CIVC 101 | Introduction to Civic Engagement | 1.0 |
| COOP 101 | Career Management and Professional Development * | 1.0 |
| UNIV B201 | Career Management | 1.0 |
| General Education Requirements | ||
| English Requirements | ||
| ENGL 101 | Composition and Rhetoric I: Inquiry and Exploratory Research | 3.0 |
| or ENGL 111 | English Composition I | |
| ENGL 102 | Composition and Rhetoric II: Advanced Research and Evidence-Based Writing | 3.0 |
| or ENGL 112 | English Composition II | |
| ENGL 103 | Composition and Rhetoric III: Themes and Genres | 3.0 |
| or ENGL 113 | English Composition III | |
| Communications Requirement | ||
| COM 230 | Techniques of Speaking | 3.0 |
| Mathematics and Statistics | ||
| Select one of the following sequences: ** | ||
| MATH 101 & MATH 102 & MATH 180 & MATH 201 | Introduction to Analysis I and Introduction to Analysis II and Discrete Computational Structures and Linear Algebra | 16.0-18.0 |
| or MATH 105 & MATH 121 & MATH 180 & MATH 201 | Algebra, Functions, and Trigonometry and Calculus I and Discrete Computational Structures and Linear Algebra | |
| or MATH 116 & MATH 117 & MATH 180 & MATH 201 | Calculus and Functions I and Calculus and Functions II and Discrete Computational Structures and Linear Algebra | |
| STAT 201 | Introduction to Business Statistics | 4.0 |
| or MATH 311 | Probability and Statistics I | |
| STAT 202 | Business Statistics II | 4.0 |
| or MATH 312 | Probability and Statistics II | |
| Computer Science | ||
| CS 150 | Computer Science Principles | 0.0-3.0 |
| or CS 164 | Introduction to Computer Science | |
| CS 171 | Computer Programming I | 0.0,3.0 |
| CS 172 | Computer Programming II | 0.0,3.0 |
| Economics Requirements | ||
| ECON 201 | Principles of Microeconomics | 4.0 |
| ECON 202 | Principles of Macroeconomics | 4.0 |
| ECON 250 | Game Theory and Applications | 4.0 |
| ECON 270 | Using Big Data to Solve Economic and Social Problems | 4.0 |
| ECON 301 | Microeconomics | 4.0 |
| ECON 321 | Macroeconomics | 4.0 |
| ECON 322 | Economics Seminar | 4.0 |
| ECON 350 | Applied Econometrics | 4.0 |
| ECON 360 | Time Series Econometrics | 4.0 |
| or ECON 370 | Experiments and Causality in Economics | |
| Data Science Requirements | ||
| CS 260 | Data Structures | 4.0 |
| CS 265 | Advanced Programming Tools and Techniques | 3.0 |
| DSCI 351 | Recommender Systems | 3.0 |
| DSCI 471 | Applied Deep Learning | 3.0 |
| INFO 101 | Introduction to Computing and Security Technology | 3.0 |
| INFO 103 | Introduction to Data Science | 3.0 |
| INFO 210 | Database Management Systems | 3.0 |
| INFO 212 | Data Science Programming I | 3.0 |
| INFO 213 | Data Science Programming II | 3.0 |
| INFO 250 | Information Visualization | 3.0 |
| INFO 323 | Cloud Computing and Big Data | 3.0 |
| INFO 332 | Exploratory Data Analytics | 3.0 |
| INFO 440 | Social Media Data Analysis | 3.0 |
| INFO 442 | Data Science Projects | 3.0 |
| Economics Electives | ||
| Select 12 credits from the following | 12.0 | |
| Survey of Economic Policy | ||
| Mathematical Models in Economics | ||
| Economics of Small Business | ||
| Economics of Happiness | ||
| Economic Ideas | ||
| Managerial Economics | ||
| International Macroeconomics | ||
| Public Finance | ||
| Labor Economics | ||
| Industrial Organization | ||
| Economic Development | ||
| Comparative Economic Systems | ||
| Mathematical Economics | ||
| Resource and Environmental Economics | ||
| Money and Banking | ||
| Time Series Econometrics | ||
| Health Economics | ||
| Behavioral Economics | ||
| Topics in Behavioral Economics | ||
| Experiments and Causality in Economics | ||
| Economic Crises: The American Experience | ||
| Special Topics in Economics | ||
| Special Topics in Economics | ||
| Special Topics in Economics | ||
| Multinational Corporations | ||
| International Trade | ||
| International Money and Finance | ||
| Regional Studies in Economic Policies and International Business | ||
| Seminar in International Business | ||
| Sport Economics | ||
| Data Science Electives | ||
| Select 6 credits from the following courses | 6.0 | |
| Mathematical Foundations of Computer Science | ||
| Artificial Intelligence | ||
| Machine Learning | ||
| Advanced Database Management Systems | ||
| Data Mining Applications | ||
| Advanced Data Analytics | ||
| Free Electives | 34.0 | |
| Total Credits | 171.0-182.0 | |
- *
Co-op cycles may vary. Students are assigned a co-op cycle (fall/winter, spring/summer, summer-only) based on their co-op program (4-year, 5-year) and major.
COOP 101 registration is determined by the co-op cycle assigned and may be scheduled in a different term. Select students may be eligible to take COOP 001 in place of COOP 101.
- **
Students should speak with an advisor about their math placement. Students who place out of the first math course in a sequence will have additional credits of free electives. Some students who select the MATH 116 & MATH 117 sequence may need a one-credit concurrent practicum course depending on their calculus exam score and summer preparatory review participation.
Writing-Intensive Course Requirements
In order to graduate, all students must pass three writing-intensive courses after their freshman year. Two writing-intensive courses must be in a student's major. The third can be in any discipline. Students are advised to take one writing-intensive class each year, beginning with the sophomore year, and to avoid “clustering” these courses near the end of their matriculation. Transfer students need to meet with an academic advisor to review the number of writing-intensive courses required to graduate.
A "WI" next to a course in this catalog may indicate that this course can fulfill a writing-intensive requirement. For the most up-to-date list of writing-intensive courses being offered, students should check the Writing Intensive Course List at the University Writing Program. Students scheduling their courses can also conduct a search for courses with the attribute "WI" to bring up a list of all writing-intensive courses available that term.
Sample Plan of Study
5 Year 3 Coop
| First Year | ||
|---|---|---|
| Fall | Credits | |
| CIVC 101 | Introduction to Civic Engagement | 1.0 |
| ECON 201 | Principles of Microeconomics | 4.0 |
| ENGL 101 or ENGL 111 | Composition and Rhetoric I: Inquiry and Exploratory Research or English Composition I | 3.0 |
| INFO 101 | Introduction to Computing and Security Technology | 3.0 |
| UNIV B101 or UNIV CI101 | The Drexel Experience or The Drexel Experience | 1.0 |
| MATH 101 | Introduction to Analysis I or Algebra, Functions, and Trigonometry or Calculus and Functions I or Calculus I | 4.0-6.0 |
| Credits | 16-18 | |
| Winter | ||
| COOP 101 | Career Management and Professional Development * | 1.0 |
| ECON 202 | Principles of Macroeconomics | 4.0 |
| ECON 270 | Using Big Data to Solve Economic and Social Problems | 4.0 |
| ENGL 102 or ENGL 112 | Composition and Rhetoric II: Advanced Research and Evidence-Based Writing or English Composition II | 3.0 |
| MATH 102 | Introduction to Analysis II or Calculus I or Calculus and Functions II or Linear Algebra | 4.0 |
| Credits | 16 | |
| Spring | ||
| CS 150 or CS 164 | Computer Science Principles or Introduction to Computer Science | 0.0-3.0 |
| ENGL 103 or ENGL 113 | Composition and Rhetoric III: Themes and Genres or English Composition III | 3.0 |
| INFO 103 | Introduction to Data Science | 3.0 |
| MATH 201 or MATH 180 | Linear Algebra or Discrete Computational Structures | 4.0 |
| Credits | 10-13 | |
| Summer | ||
| VACATION | ||
| Credits | 0 | |
| Second Year | ||
| Fall | ||
| COOP EXPERIENCE | ||
| Credits | 0 | |
| Winter | ||
| COOP EXPERIENCE | ||
| Credits | 0 | |
| Spring | ||
| CS 171 | Computer Programming I | 0.0,3.0 |
| ECON 301 | Microeconomics | 4.0 |
| INFO 210 | Database Management Systems | 3.0 |
| STAT 201 or MATH 311 | Introduction to Business Statistics or Probability and Statistics I | 4.0 |
| MATH 180 | Discrete Computational Structures † | 4.0 |
| Credits | 15-18 | |
| Summer | ||
| COM 230 | Techniques of Speaking | 3.0 |
| CS 172 | Computer Programming II | 0.0,3.0 |
| ECON 250 | Game Theory and Applications | 4.0 |
| STAT 202 or MATH 312 | Business Statistics II or Probability and Statistics II | 4.0 |
| Credits | 11-14 | |
| Third Year | ||
| Fall | ||
| COOP EXPERIENCE | ||
| Credits | 0 | |
| Winter | ||
| COOP EXPERIENCE | ||
| Credits | 0 | |
| Spring | ||
| CS 265 | Advanced Programming Tools and Techniques | 3.0 |
| ECON 321 | Macroeconomics | 4.0 |
| ECON 350 | Applied Econometrics | 4.0 |
| INFO 212 | Data Science Programming I | 3.0 |
| INFO 440 | Social Media Data Analysis | 3.0 |
| Credits | 17 | |
| Summer | ||
| CS 260 | Data Structures | 4.0 |
| INFO 213 | Data Science Programming II | 3.0 |
| INFO 250 | Information Visualization | 3.0 |
| ECON Elective | 4.0 | |
| Credits | 14 | |
| Fourth Year | ||
| Fall | ||
| COOP EXPERIENCE | ||
| Credits | 0 | |
| Winter | ||
| COOP EXPERIENCE | ||
| Credits | 0 | |
| Spring | ||
| DSCI 351 | Recommender Systems | 3.0 |
| INFO 323 | Cloud Computing and Big Data | 3.0 |
| ECON Elective | 4.0 | |
| Free Elective | 4.0 | |
| Credits | 14 | |
| Summer | ||
| DSCI 471 | Applied Deep Learning | 3.0 |
| INFO 332 | Exploratory Data Analytics | 3.0 |
| Free Elective | 8.0 | |
| Credits | 14 | |
| Fifth Year | ||
| Fall | ||
| ECON 360 or ECON 370 | Time Series Econometrics or Experiments and Causality in Economics | 4.0 |
| Free Electives | 7.0 | |
| Data Science Elective | 3.0 | |
| Credits | 14 | |
| Winter | ||
| UNIV B201 | Career Management | 1.0 |
| Data Science Elective | 3.0 | |
| ECON Elective | 4.0 | |
| Free Elective | 7.0 | |
| Credits | 15 | |
| Spring | ||
| ECON 322 | Economics Seminar | 4.0 |
| INFO 442 | Data Science Projects | 3.0 |
| Free Elective | 8.0 | |
| Credits | 15 | |
| Total Credits | 171-182 | |
- *
Co-op cycles may vary. Students are assigned a co-op cycle (fall/winter, spring/summer, summer-only) based on their co-op program (4-year, 5-year) and major.
COOP 101 registration is determined by the co-op cycle assigned and may be scheduled in a different term. Select students may be eligible to take COOP 001 in place of COOP 101.
- †
Students who placed out of the first course in their math sequence will have additional credits of free electives.
4 Year 1 Coop
| First Year | ||
|---|---|---|
| Fall | Credits | |
| UNIV B101 or UNIV CI101 | The Drexel Experience or The Drexel Experience | 1.0 |
| CIVC 101 | Introduction to Civic Engagement | 1.0 |
| ENGL 101 or ENGL 111 | Composition and Rhetoric I: Inquiry and Exploratory Research or English Composition I | 3.0 |
| INFO 101 | Introduction to Computing and Security Technology | 3.0 |
| MATH 101 | Introduction to Analysis I or Algebra, Functions, and Trigonometry or Calculus and Functions I or Calculus I | 4.0-6.0 |
| ECON 201 | Principles of Microeconomics | 4.0 |
| Credits | 16-18 | |
| Winter | ||
| ENGL 102 or ENGL 112 | Composition and Rhetoric II: Advanced Research and Evidence-Based Writing or English Composition II | 3.0 |
| ECON 202 | Principles of Macroeconomics | 4.0 |
| MATH 102 | Introduction to Analysis II or Calculus I or Calculus and Functions II or Linear Algebra | 4.0 |
| ECON 270 | Using Big Data to Solve Economic and Social Problems | 4.0 |
| Credits | 15 | |
| Spring | ||
| ENGL 103 or ENGL 113 | Composition and Rhetoric III: Themes and Genres or English Composition III | 3.0 |
| CS 150 or CS 164 | Computer Science Principles or Introduction to Computer Science | 3.0 |
| MATH 201 or MATH 180 | Linear Algebra or Discrete Computational Structures | 4.0 |
| INFO 103 | Introduction to Data Science | 3.0 |
| Free Elective | 3.0 | |
| Credits | 16 | |
| Summer | ||
| VACATION | ||
| Credits | 0 | |
| Second Year | ||
| Fall | ||
| CS 171 | Computer Programming I | 3.0 |
| STAT 201 or MATH 311 | Introduction to Business Statistics or Probability and Statistics I | 4.0 |
| ECON 301 | Microeconomics | 4.0 |
| INFO 210 | Database Management Systems | 3.0 |
| MATH 180 | Discrete Computational Structures † | 4.0 |
| Credits | 18 | |
| Winter | ||
| CS 172 | Computer Programming II | 0.0,3.0 |
| ECON 321 | Macroeconomics | 4.0 |
| STAT 202 or MATH 312 | Business Statistics II or Probability and Statistics II | 4.0 |
| COOP 101 | Career Management and Professional Development | 1.0 |
| Credits | 9-12 | |
| Spring | ||
| ECON 350 | Applied Econometrics | 4.0 |
| COM 230 | Techniques of Speaking | 3.0 |
| INFO 212 | Data Science Programming I | 3.0 |
| CS 265 | Advanced Programming Tools and Techniques | 3.0 |
| Credits | 13 | |
| Summer | ||
| INFO 213 | Data Science Programming II | 3.0 |
| INFO 250 | Information Visualization | 3.0 |
| CS 260 | Data Structures | 4.0 |
| Free Electives | 6.0 | |
| Credits | 16 | |
| Third Year | ||
| Fall | ||
| COOP EXPERIENCE | ||
| Credits | 0 | |
| Winter | ||
| COOP EXPERIENCE | ||
| Credits | 0 | |
| Spring | ||
| ECON 370 or ECON 360 | Experiments and Causality in Economics or Time Series Econometrics | 4.0 |
| INFO 323 | Cloud Computing and Big Data | 3.0 |
| INFO 440 | Social Media Data Analysis | 3.0 |
| Econ Elective | 4.0 | |
| Credits | 14 | |
| Summer | ||
| ECON 250 | Game Theory and Applications | 4.0 |
| INFO 332 | Exploratory Data Analytics | 3.0 |
| Free Electives | 7.0 | |
| Credits | 14 | |
| Fourth Year | ||
| Fall | ||
| UNIV B201 | Career Management | 1.0 |
| ECON 322 | Economics Seminar | 4.0 |
| Econ Elective | 4.0 | |
| Data Science Elective | 3.0 | |
| Free Elective | 3.0 | |
| Credits | 15 | |
| Winter | ||
| DSCI 351 | Recommender Systems | 3.0 |
| Data Science Elective | 3.0 | |
| Econ Elective | 4.0 | |
| Free Electives | 6.0 | |
| Credits | 16 | |
| Spring | ||
| DSCI 471 | Applied Deep Learning | 3.0 |
| INFO 442 | Data Science Projects | 3.0 |
| Free Electives | 9.0 | |
| Credits | 15 | |
| Total Credits | 177-182 | |
- *
Co-op cycles may vary. Students are assigned a co-op cycle (fall/winter, spring/summer, summer-only) based on their co-op program (4-year, 5-year) and major.
COOP 101 registration is determined by the co-op cycle assigned and may be scheduled in a different term. Select students may be eligible to take COOP 001 in place of COOP 101.
- †
Students who placed out of the first course in their math sequence will have additional credits of free electives.
