Yale’s Bachelor of Science in Computer Science and Mathematics is a rigorous interdisciplinary program that merges deep mathematical theory with powerful computational tools. Housed jointly in the Departments of Computer Science and Mathematics, the major emphasizes logic, algorithmic thinking, proof-based problem solving, and computational modeling.
This degree is ideal for students aiming to pursue graduate studies or research-intensive careers requiring a strong foundation in both fields.
Core Curriculum Components
Mathematics Foundation
MATH 120: Multivariable Calculus
MATH 225/226: Linear Algebra and Abstract Algebra
MATH 255: Real Analysis I
MATH 244: Discrete Mathematics
MATH 230/231: Fields & Galois Theory (advanced electives)
Computer Science Core
CPSC 201: Introduction to Computer Science
CPSC 223: Data Structures and Programming Techniques
CPSC 365: Design and Analysis of Algorithms
CPSC 323: Systems Programming and Computer Architecture
CPSC 440: Theory of Computation
Integration & Interdisciplinary Courses
Students must take multiple courses that explicitly bridge math and CS, including:
CPSC 366: Mathematical Tools for Computer Science
CPSC 478 / MATH 377: Introduction to Cryptography
CPSC 468: Artificial Intelligence
CPSC 476: Computational Vision and Perception (for advanced electives)
Capstone Requirement
Students complete a senior project (CPSC 490 or MATH 475), which may include research, theoretical analysis, or applied systems work combining both disciplines.
Additional Requirements
Writing-Intensive Courses (W): Fulfilled by courses like CPSC 490 or mathematical seminars requiring formal exposition.
Advanced Theoretical Electives: Students are encouraged to pursue topics such as logic, topology, or advanced algorithms.
Yale encourages Computer Science and Mathematics students to apply their knowledge through research, internships, teaching, and collaborative learning:
Undergraduate Research
Yale’s Directed Independent Study (CPSC 471/MATH 470) allows students to pursue original research with faculty mentors in fields like:
Complexity theory
Computational algebra
Machine learning theory
Topological data analysis
Algorithmic game theory
Students often present at conferences (e.g., SIGCSE, SIAM, NeurIPS) and publish in academic journals.
Capstone & Senior Project
Senior projects often blend theoretical and applied work, such as:
Cryptographic protocols grounded in number theory
Efficient algorithms for graph problems
Real-world applications of combinatorics or optimization
Teaching & Mentorship
Students may serve as peer tutors, lab assistants, or mentors for the Yale Undergraduate Math Society or Women in Computer Science, helping underclassmen through workshops, competitions, and community events.
Hackathons & Competitions
Yale Hack
International Collegiate Programming Contest (ICPC)
Mathematical Contest in Modeling (MCM)
Putnam Competition
Participation fosters critical thinking and team-based problem solving.
Internships
Yale students pursue internships with:
Tech firms (e.g., Google, Meta, Palantir, Amazon)
Quant firms (e.g., Jane Street, Two Sigma, Citadel)
National labs and NGOs working on computation in biology, economics, or security
Government and policy institutions (e.g., NIST, US Digital Service)
Graduates of Yale’s CS+Math program are recognized for their mathematical precision, computational fluency, and creative problem-solving. Whether entering academia or industry, they bring rigorous thought and adaptability to evolving challenges in technology and science.
Career Progression Examples
Software Engineer → Principal Engineer → Chief Technology Officer
Machine Learning Engineer → Research Lead → Director of AI
Quant Analyst → Portfolio Manager → Head of Quantitative Research
PhD Researcher → Assistant Professor → Department Chair
Math/CS Policy Analyst → Technology Advisor → Chief Data Ethics Officer
Graduate Study
Many pursue advanced degrees at top-tier institutions in:
Theoretical Computer Science
Applied Mathematics
Machine Learning or Statistics
Cryptography and Security
Mathematical Economics
Philosophy of Computation and Logic
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