Joint Majors

As the most technically rigorous curriculum jointly offered by the Department of Data and Decision Sciences and the Department of Mathematics, the Applied Math and Stats (AMS) major provides the necessary building blocks for statistical analysis as well as the tools and conceptual foundations for quantitative research and empirical quantitative work.

This major will prepare you for:

• Data-oriented or quantitative fields
• Becoming a "Type B" Data Scientist (data engineer)
• Graduate school in statistics or applied math, actuarial science, or financial mathematics
• Interdisciplinary graduate training in business analytics, the social sciences (particularly economics), physical and natural sciences, or engineering

What distinguishes AMS from similar majors?

There are three key features of the AMS major:

1. Introduction to Scientific Methods will change how you think and help you approach statistical questions with an eye for cause and effect
2. The major focuses on practical applications but isn't limited to any one field, so if you want to keep your options open, your AMS coursework will be broadly applicable to a range of disciplines
3. A common core of courses (like Intro to Statistical Computing and Regression Analysis) is shared across Data Science majors, but specific courses in the AMS major emphasize mathematical foundations

Total credits towards AMS: 56+ required

Data Science Courses

• MATH 362 is a prerequisite for Data Science 220

MATH Courses

• MATH 221 or MATH 321 - Linear Algebra or Abstract Vector Spaces
• CS 170 or Math 170 -  Intro to Computer Science I or Intro to Scientific Computing

Elective Courses

• Data Science electives include 300- and 400-level lecture and seminar style classes of 3+ credit hours
• Data Science 398R, 495A, 496R, 497R, and 499R do not satisfy the Data Science elective requirement
• MATH electives include your choice of the following:
  • MATH 330: Intro to Combinatorics
  • MATH 345: Math Modeling
  • MATH 346: Intro to Optimization Theory
  • MATH 351: Partial Differential Equations
  • MATH 352: PDEs in Action
  • MATH 411: Real Analysis I
  • MATH 412: Real Analysis II
• CS 171 or CS / MATH course at 200+ level. The additional CS / MATH course cannot include courses already fulfilled in a previous category. MATH 210 is also excluded.

Overview of the BBA + Data Science (BBA+DATASCI) Secondary Major

The Department of Data and Decision Sciences in Emory College and the Bachelor of Business Administration program in the Goizueta Business School have joined forces to offer a BBA with a secondary major in Data Science. This partnership couples the rigor of the BBA program with a secondary major in Data Sciences.

What Distinguishes BBA+DATASCI from similar majors?

• The purpose of this degree program is to enhance the quantitative and analytic preparation of students choosing to study business at Emory. While pursuing a BBA alone will provide students an excellent foundation in practical approaches to data in business, adding a Data Science secondary major adds additional opportunities for data training
• If you are a student in the Business School, completing a BBA+DATASCI major requires fewer extra courses than completing a DATASCI major with a college track, which makes it more accessible and practical for completing the extra requirement

This major prepares you for:

• Data-oriented business careers, including marketing analytics, strategy and management consulting, decision analysis/operations, and finance
• Graduate training in business
• Interdisciplinary graduate training, for example in sociology, economics, or political science

As members of a society, you have the opportunity and the privilege to affect change on pressing issues of our time. Whether you're interested in education policy, housing policy, or beyond, the major in Public Policy Analysis is a joint major with Political Science and combines the rigor of a data science degree with an emphasis on public policy.

What distinguishes PPA from similar majors?

• The main reason to choose PPA is that Data Science offers the strongest technical training of any public policy education not only at Emory, but around the country. Public Policy is an increasingly quantitative space and the technical skills provided by the Department of Data and Decision Sciences are increasingly critical to policy analysis and advocacy.
• The PPA major uniquely prepares students to better understand public policy, to assess policy and the context in which it exists, and to advocate for policy advancement and reforms

This major prepares you for:

• Employment in many data- or quantitatively-oriented policy arenas (e.g., non-profit, education, government, social work, etc.)
• Graduate study in public policy, law, political science, or business
• Interdisciplinary graduate training, for example in the social sciences or environmental sciences

Total credits towards PPA: 51+ required

Data Science Courses

• MATH 111 and MATH 221 are prerequisites to the Data Science major and do not count towards major GPA

Elective Courses

• Data Science electives include 300- and 400-level lecture and seminar style classes of 3+ credit hours.
• Data Science 398R, 495A, 496R, 497R, and 499R do not satisfy the Data Science elective requirement.
• PPA electives may be selected from approved ECON, ENVS, HIST, POLS, or SOC offerings; up-to-date elective options may be found on the Political Science website
• African American Studies Electives
  
  • AAS 385 Blacks and Housing Policy
  • AAS 385 Race, Place, and Political Economy
• Economics Electives
  
  • ECON 231 Intro to Global Trade and Finance
  • ECON 309 Contemporary Economic Issues
  • ECON 330 Collective Bargaining and Public Policy
  • ECON 341 Business and Government
  • ECON 356 Development of the US Economy
  • ECON 362 Economic Development
  • ECON 365 Environmental Economics and Policy
  • ECON 385 The Political Economy of China
  • ECON 390 The Political Econ of the Middle East
• Environmental Science Electives
  • ENVS 225 Institutions & The Environment
  • ENVS 224 Economy and the Environment
  • ENVS 227 Environmental Policy
  • ENVS 324 Environmental Economics
  • ENVS 326 Climate Change and Society
  • ENVS 365 Urban Geography
  • ENVS 389 Urban Food Security
• Health Electives
  • HLTH 370 Health Policy
  • HLTH 373 Delivering Health
• History Electives
  • HIST 385 Wealth & Poverty in the US
• Political Science Electives
  • POLS 227 Environmental Policy
  • POLS 309 Survey Research & Political Analysis
  • POLS 316 Foreign Policy of the U.S.
  • POLS 319 International Political Economy
  • POLS 321 Comparative Political Economy (POLS 394W)
  • POLS 335 Nations and Nationalism
  • POLS 339 Politics and the Environment
  • POLS 342 Congressional Politics
  • POLS 342 Congressional Politics
  • POLS 343 Federalism and Intergovernmental Relations
  • POLS 350 American Legal System
  • POLS 354 Criminal Justice
  • POLS 355 Nonprofits and Politics
  • POLS 357 Gender Politics
  • POLS 362 Executive Branch Governance
  • POLS 366 Poverty in America
  • POLS 367 Urban Politics
  • POLS 368 Urban Public Policy
  • POLS 370A Community Building and Social Change
  • POLS 370B Planning Community Initiatives
  • POLS 384 Environmental Policy
  • POLS 385 Topic: The Law & Politics of Immigration
  • POLS 385 State Politics and Policy
  • POLS 394W Politics of Public Health
  • POLS 486 Washington Semester
  • POLS 490 RSCH: Political Economy of Public Policy
  • POLS 494 Gender, Race, and Political Representation
  • POLS 494 Evidence-based Policymaking
  • POLS 494 Globalization and Human Rights
  • POLS 494W Politics and Punishment
  • POLS 494W Politics of Public Health
  • POLS 496 Internship in Political Science
• Sociology Electives
  • SOC 201 Organizations and Society
  • SOC 230 Sociological Aspects of Health/Illness
  • SOC 307 Sociology of Education
  • SOC 343 Mass Media & Social Influence
  • SOC 350 Sociology of Law
  • SOC/ENVS 389 Urban Food Security
  • SOC 390 Study Abroad: Health Care & Society Sem
  • SOC 446W Big/Small Data and Visualization