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Computer Science-Economics

The joint Computer Science-Economics concentration exposes students to the theoretical and practical connections between computer science and economics. It prepares students for professional careers that incorporate aspects of economics and computer technology and for academic careers conducting research in areas that emphasize the overlap between the two fields. Concentrators may choose to pursue either the A.B. or the Sc.B. degree. While the A.B. degree allows students to explore the two disciplines by taking advanced courses in both departments, its smaller number of required courses is compatible with a liberal education. The Sc.B. degree achieves greater depth in both computer science and economics by requiring more courses, and it offers students the opportunity to creatively integrate both disciplines through a design requirement. If you are interested in declaring a concentration in Computer Science-Economics, please refer to this page for more information regarding the process. For more information about the CS Pathways, see this page.

Standard Program for the Sc.B. degree.

Prerequisites (3 courses):
Single Variable Calculus, Part II
Linear Algebra
Linear Algebra With Theory
Coding the Matrix: An Introduction to Linear Algebra for Computer Science
Principles of Economics
Required Courses: 17 courses: 8 Computer Science, 8 Economics, and a Capstone
CSCI 1450Advanced Introduction to Probability for Computing and Data Science 11
or APMA 1650 Statistical Inference I
or APMA 1655 Honors Statistical Inference I
Select one of the following Series:2
Series A
Introduction to Object-Oriented Programming and Computer Science
and Program Design with Data Structures and Algorithms
Series B
Computer Science: An Integrated Introduction
and Program Design with Data Structures and Algorithms
Series C
Accelerated Introduction to Computer Science (and an additional CS course not otherwise used to satisfy a concentration requirement; this course may be CSCI 0200, an intermediate-level CS course, or a 1000-level course.)
Series D
Computing Foundations: Data
and Computing Foundations: Program Organization
and Program Design with Data Structures and Algorithms
Two of the following Computer Science Foundations courses: 2
a. Algorithms/Theory Foundations
CSCI 0500
Data Structures, Algorithms, and Intractability: An Introduction
Theory of Computation
Probabilistic Methods in Computer Science
Design and Analysis of Algorithms
b. AI/Machine Learning/Data Science Foundations
Artificial Intelligence
Machine Learning
Computer Vision
Computational Linguistics
Deep Learning
Deep Learning in Genomics
Introduction to Robotics
c. Systems Foundations
Fundamentals of Computer Systems
Introduction to Computer Systems
d. Math Foundations
Statistical Inference I
Advanced Introduction to Probability for Computing and Data Science
Probability
or another APMA/MATH course that features probability
Three 1000-level CSCI courses, which cannot include arts/policy/ humanities courses. One of these can be an additional Foundations course.3
ECON 1130Intermediate Microeconomics (Mathematical) 21
ECON 1210Intermediate Macroeconomics1
ECON 1630Mathematical Econometrics I1
Three courses from the "mathematical economics" group (CSCI 1951K can be counted as one of them, if it has not been used to satisfy the computer science requirements of the concentration and if the student has taken either ECON 1470 or ECON 1870):3
Welfare Economics and Social Choice Theory
Advanced Macroeconomics: Monetary, Fiscal, and Stabilization Policies
Unemployment: Models and Policies
Bargaining Theory and Applications
Theory of Market Design
Topics in Macroeconomics, Development and International Economics
Mathematical Econometrics II
Big Data
Advanced Topics in Econometrics
Machine Learning, Text Analysis, and Economics
Investments II
Crisis Economics
Economics in the Laboratory
Theory of Behavioral Economics
The Theory of General Equilibrium
Game Theory and Applications to Economics
Two additional 1000-level Economics courses excluding 1620, 1960, 1970 32
One capstone course in either CS or Economics: a one-semester course, normally taken in the student's last semester undergraduate year, in which the student (or group of students) use a significant portion of their undergraduate education, broadly interpreted, in studying some current topic (preferably at the intersection of computer science and economics) in depth, to produce a culminating artifact such as a paper or software project. A senior thesis, which involved two semesters of work, may count as a capstone. 1
Total Credits17

Standard Program for the A.B. degree:

Prerequisites (3 courses):
Single Variable Calculus, Part II
Linear Algebra
Linear Algebra With Theory
Coding the Matrix: An Introduction to Linear Algebra for Computer Science
Principles of Economics
Required Courses: 13 courses: 7 Computer Science and 6 Economics
CSCI 1450Advanced Introduction to Probability for Computing and Data Science1
or APMA 1650 Statistical Inference I
or APMA 1655 Honors Statistical Inference I
Select one of the following series:2
Series A
Introduction to Object-Oriented Programming and Computer Science
and Introduction to Algorithms and Data Structures
Series B
Computer Science: An Integrated Introduction
and Computer Science: An Integrated Introduction
Series C
Accelerated Introduction to Computer Science (and an additional CS course not otherwise used to satisfy a concentration requirement; this course may be CSCI 0200, an intermediate-level course, or a 1000-level course)
Series D
Computing Foundations: Data
and Computer Science: An Integrated Introduction
Two Computer Science Foundational Courses from the following: 2
a. Algorithms/Theory Foundations
CSCI 0500
Data Structures, Algorithms, and Intractability: An Introduction
Theory of Computation
Probabilistic Methods in Computer Science
Design and Analysis of Algorithms
b. AI/Machine Learning/Data Science Foundations
Artificial Intelligence
Machine Learning
Computer Vision
Computational Linguistics
Deep Learning
Deep Learning in Genomics
Introduction to Robotics
c. Systems Foundations
Fundamentals of Computer Systems
Introduction to Computer Systems
d. Math Foundations
Statistical Inference I
Advanced Introduction to Probability for Computing and Data Science
Probability
or another APMA/MATH course that features probability
2 1000-level CSCI courses, which cannot include arts/policy/humanities courses. One of these can be an additional Foundations course.2
ECON 1130Intermediate Microeconomics (Mathematical) 11
ECON 1210Intermediate Macroeconomics1
ECON 1630Mathematical Econometrics I1
Three courses from the "mathematical-economics" group: 23
Welfare Economics and Social Choice Theory
Advanced Macroeconomics: Monetary, Fiscal, and Stabilization Policies
Unemployment: Models and Policies
Bargaining Theory and Applications
Theory of Market Design
Topics in Macroeconomics, Development and International Economics
Mathematical Econometrics II
Big Data
Advanced Topics in Econometrics
Machine Learning, Text Analysis, and Economics
Investments II
Crisis Economics
Economics in the Laboratory
Theory of Behavioral Economics
The Theory of General Equilibrium
Game Theory and Applications to Economics
or any graduate Economics course 3
Total Credits13

Honors

Students who meet stated requirements are eligible to write an honors thesis in their senior year.  Students should consult the listed honors requirements of whichever of the two departments their primary thesis advisor belongs to, at the respective departments' websites. If the primary thesis advisor belongs to Economics (Computer Science), then students must have a reader in the Computer Science (respectively, Economics) department.

Professional Track

The requirements for the professional track include all those of the standard track, as well as the following:

Students must complete full-time professional experiences doing work that is related to their concentration programs, totaling 2-6 months, whereby each internship must be at least one month in duration in cases where students choose to do more than one internship experience. Such work is normally done at a company, but may also be at a university under the supervision of a faculty member. Internships that take place between the end of the fall and the start of the spring semesters cannot be used to fulfill this requirement.

On completion of each professional experience, the student must write and upload to ASK a reflective essay about the experience addressing the following prompts, to be approved by the student's concentration advisor:

  • Which courses were put to use in your summer's work? Which topics, in particular, were important?
  • In retrospect, which courses should you have taken before embarking on your summer experience? What are the topics from these courses that would have helped you over the summer if you had been more familiar with them?
  • Are there topics you should have been familiar with in preparation for your summer experience, but are not taught at Brown? What are these topics?
  • What did you learn from the experience that probably could not have been picked up from course work?
  • Is the sort of work you did over the summer something you would like to continue doing once you graduate? Explain.
  • Would you recommend your summer experience to other Brown students? Explain.