Bachelor of Science in Computer Science Economics and Data Science

4 Years On Campus Bachelors Program

Massachusetts Institute of Technology

Program Overview

MIT’s Course 6-14 is an interdisciplinary program that combines the analytical rigor of computer science and data science with the empirical foundations of economics. This unique blend prepares students to tackle complex real-world problems using computational tools and economic reasoning.

Core Curriculum Components

  • Mathematics

    • 18.06: Linear Algebra

    • 6.1200[J]: Mathematics for Computer Science

  • Computer Science

    • 6.100A: Introduction to Computer Science Programming in Python

    • 6.1010: Fundamentals of Programming

    • 6.1210: Introduction to Algorithms

    • 6.1220[J]: Design and Analysis of Algorithms

  • Economics

    • 14.01: Principles of Microeconomics

    • 14.32: Econometric Data Science

  • Probability and Statistics

    • Options include:

      • 6.3700: Introduction to Probability

      • 14.30: Introduction to Statistical Methods in Economics

      • 18.600: Probability and Random Variables

  • Data Science

    • 6.3900: Introduction to Machine Learning

  • Communication-Intensive Subjects (CI-M)

    • 6.UAT: Oral Communication

    • 14.05: Intermediate Macroeconomics

    • 14.18: Mathematical Economic Modeling

    • 14.33: Research and Communication in Economics

Experiential Learning (Research, Projects, Internships etc.)

MIT emphasizes hands-on learning, ensuring that students not only grasp theoretical concepts but also apply them in real-world contexts.​

  • Undergraduate Research Opportunities Program (UROP)

    • Engage in cutting-edge research projects across various labs, allowing students to contribute to ongoing scientific inquiries.​

  • MIT International Science and Technology Initiatives (MISTI)

    • Gain global experience through internships and research abroad, applying skills in diverse cultural and professional settings.​

  • Entrepreneurship & Innovation Programs

    • Participate in initiatives like the MIT Sandbox Innovation Fund and the Martin Trust Center for MIT Entrepreneurship to develop and launch startups.​

  • Public Service Center (PSC) Fellowships

    • Apply technical skills to address societal challenges through community service projects and fellowships.​

  • Capstone Projects

    • Undertake comprehensive projects that synthesize learning across disciplines, often in collaboration with industry partners or research labs.​

Explore more opportunities through the MIT (ELO) platform.​

Progression & Future Opportunities

Graduates of Course 6-14 are uniquely positioned at the intersection of computer science, economics, and data science, opening doors to diverse career paths:​

Technology & Data Science

  • Data Scientist

  • Machine Learning Engineer

  • Software Developer

  • Product Manager​

Finance & Consulting

  • Quantitative Analyst

  • Financial Engineer

  • Management Consultant

  • Economic Analyst

Public Policy & Research

  • Policy Advisor

  • Research Scientist

  • Academic Researcher

  • Think Tank Analyst

Entrepreneurship

  • Startup Founder

  • Innovation Strategist

  • Tech Entrepreneur

Students with a strong academic record can opt for the integrated MEng program, extending their studies by a year to gain deeper expertise:​

  • Advanced Coursework

    • At least 42 units of graduate subjects, including concentrations in economics and computer science.​

  • Thesis Research

    • A substantial research project culminating in a thesis, allowing students to contribute original findings to the field.​

  • Professional Perspective Internship

    • A component designed to provide industry exposure and practical experience.​

 

 

Program Key Stats

$61,990
$ 75
Aug Intake : RD 6th Jan EA/ED 1st Nov


8 %
No
Yes

Eligibility Criteria

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

1510 - 1580
34 - 36
7.0
90

Additional Information & Requirements

Career Options

  • Technology & Data Science: Data Scientist
  • Machine Learning Engineer
  • Software Developer
  • Data Engineer
  • AI/ML Product Developer Finance & Quantitative Analysis: Quantitative Analyst
  • Financial Engineer
  • Risk Analyst
  • Algorithmic Trader
  • Investment Strategist Consulting & Business Analytics: Management Consultant
  • Strategy Consultant (Tech Focus)
  • Business Analyst (Data Focus)
  • Economic Consultant
  • Operations Research Analyst Economics & Public Policy: Economic Analyst
  • Policy Advisor
  • Research Economist
  • Data-Driven Policy Consultant
  • Think Tank Researcher Product & Program Management: Technical Product Manager
  • Data Product Manager
  • Program Manager (Tech Firms)
  • Digital Strategy Manager Entrepreneurship & Innovation: Startup Founder (FinTech / EdTech / Data Analytics)
  • Innovation Strategist
  • Tech Entrepreneur
  • Venture Analyst (Tech/AI-focused VC firms) Further Studies: MS or PhD in Computer Science
  • MS or PhD in Data Science
  • MS or PhD in Economics
  • MS or PhD in Public Policy with Data Science Focus
  • MBA (for Business Leadership / Product Management) Long-Term Growth: Technology: Data Scientist → Lead Data Scientist → Head of AI
  • Finance: Quant Analyst → VP Quant Research → Chief Risk Officer
  • Product & Business: Product Manager → Director of Product → VP Product
  • Consulting: Consultant → Engagement Manager → Partner
  • Entrepreneurship: Founder → Series A → Series B → CEO

Book Free Session with Our Admission Experts

Admission Experts