BS Computer Science and Mathematics

4 Years On Campus Bachelors Program

Yale University

Program Overview

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.

Experiential Learning (Research, Projects, Internships etc.)

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)

Progression & Future Opportunities

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

Program Key Stats

$67,250
$ 80
Aug Intake : RD 2nd Jan EA/ED 1st Nov


5 %
No
Yes

Eligibility Criteria

AAA - A*A*A
3.5 - 4.0
38 - 42
90 - 95

1500 - 1580
33 - 35
7.0
100

Additional Information & Requirements

Career Options

  • Graduates of Yale’s Bachelor of Science in Computer Science and Mathematics possess a rare combination of mathematical rigor and computational fluency
  • preparing them for influential careers in research
  • technology development
  • finance
  • data science
  • and beyond
  • The interdisciplinary nature of the degree nurtures analytical thinkers who can tackle complex
  • abstract problems and apply theory to real-world challenges
  • Technology & Software Engineering Software Engineer: Designing reliable and efficient software systems using strong theoretical underpinnings
  • Full Stack Developer: Building scalable front-end and back-end infrastructure
  • Cloud Computing Engineer: Architecting distributed systems and cloud-native applications
  • Systems Programmer: Creating core system tools and performance-critical software
  • Artificial Intelligence & Data Science Machine Learning Engineer: Building and refining predictive models using statistical methods
  • AI Researcher: Advancing intelligent systems using formal logic and mathematical learning theory
  • Data Scientist: Analyzing complex data sets to guide decisions and policy
  • Computational Mathematician: Solving applied problems in physics
  • engineering
  • or economics through numerical methods
  • Finance & Quantitative Fields Quantitative Analyst (Quant): Developing mathematical models to guide investment strategies
  • Algorithmic Trader: Designing and optimizing trading algorithms
  • Financial Engineer: Applying stochastic models and programming in financial systems
  • Risk Analyst: Using probabilistic models to evaluate financial risk
  • Research & Academia Theoretical Computer Scientist: Conducting fundamental research in algorithms
  • cryptography
  • or complexity theory
  • Mathematical Logician: Exploring foundational logic and computation
  • PhD Student in CS
  • Mathematics
  • or Interdisciplinary Fields Mathematics Educator or University Lecturer Other Emerging Roles Cryptographer / Cybersecurity Analyst: Developing encryption protocols and secure systems
  • Operations Research Analyst: Optimizing logistics and organizational systems
  • Policy Advisor (AI or Data Policy): Using quantitative methods to inform national and global tech policy

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