The specialization in Data Analytics and Quantitative Analysis (DAQA) provides opportunities to pursue advanced work in computational and data analytics, econometrics and quantitative analysis and to apply these techniques to a broad array of policy and management issues.
Cristian Pop-Eleches, Professor of International and Public Affairs
Specialization Co-Director
cp2124@columbia.edu
Alan Yang, Senior Lecturer in the Discipline of International and Public Affairs
Specialization Co-Director
asy2@columbia.edu
Marie Gugnishev
Specialization Coordinator
mg4441@columbia.edu
Cristian Pop-Eleches, Professor of International and Public Affairs; Co-Director of the Data Analytics and Quantitative Analysis Specialization
Alan Yang, Senior Lecturer in the Discipline of International and Public Affairs; Co-Director of the Data Analytics and Quantitative Analysis Specialization
Douglas Almond, Professor of International and Public Affairs
Flavio Bartmann, Adjunct Professor of International and Public Affairs
Daniel Björkegren, Assistant Professor of International and Public Affairs
Aidan Feldman, Lecturer (part-time) of International and Public Affairs
Poranee 'Pam' Kingpetcharat, Lecturer (part-time) of International and Public Affairs
Rebecca Krisel, Lecturer (part-time) of International and Public Affairs
Emmanuel Letouze, Adjunct Associate Professor of International and Public Affairs
Sameer Maskey, Adjunct Associate Professor of International and Public Affairs
Tamar Mitts, Assistant Professor of International and Public Affairs
Jeffrey Shrader, Assistant Professor of International and Public Affairs
Harold Stolper, Lecturer in Discipline of International and Public Affairs
Douglas Williamson, Adjunct Associate Professor of International and Public Affairs
Mike Zhu, Adjunct Assistant Professor of International and Public Affairs
The Data Analytics & Quantitative Analysis (DAQA) Specialization requires 9 points, consisting of one required three-point course, and six-points in either quantitative analysis or data analytics electives.
In addition to these requirements, DAQA students are required to complete the SIPA U6400 / SIPA U6401 sequence of economics in the MIA and MPA core and SIPA U6500 Quantitative Analysis I for International and Public Affairs to qualify for the DAQA Specialization. Additionally, students must earn a minimum grade of B- in SIPA U6400 and SIPA U6500. It is strongly recommended that students complete SIPA U6500 during their first semester.
Questions should be directed to Marie Gugnishev, Coordinator of the DAQA Specialization, at mg4441@columbia.edu.
SIPA U6400 Microeconomic Analysis for International and Public Affairs*
SIPA U6401 Macroeconomic Analysis for International and Public Affairs
SIPA U6500 Quantitative Analysis I for International and Public Affairs*
*Minimum grade requirement of B-
SIPA U6501 Quantitative Analysis II for International and Public Affairs
3 Credits of an Advanced Course
3 Credits of elective courses
Due to International Economic Policy requiring SIPA U6501 as a core course, students in this concentration must instead take an additional DAQA elective course to fulfill specialization requirements for a total of 9 credits in DAQA electives:
3 credits of an Advanced Course
6 credits of elective courses
| Code | Title | Points |
|---|---|---|
| Points | ||
| SIPA U6501 | Quantitative Analysis II for International and Public Affairs | 3.00 |
| Code | Title | Points |
|---|---|---|
| Points | ||
Advanced Courses | ||
| INAF U6599 | Quant III: Labor Economics For Policy Students | 3.00 |
| INAF U6604 | Applied Econometrics | 3.00 |
| INAF U6608 | Economics of Education Policy | 3.00 |
| INAF U6614 | Data Analysis for Policy Research Using R | 3.00 |
| INAF U8145 | Advanced Economic Development for International Affairs | 3.00 |
| INAF U8305 | Conducting Empirical Research in Economics | 3.00 |
| INAF U8360 | Economic Measurement of Discrimination | 3.00 |
| PEPM U6640 | Macroeconometrics | 3.00 |
| PUAF U8516 | Time Series Analysis | 3.00 |
| SIPA U8500 | Quantitative Methods in Program Evaluation and Policy Research | 3.00 |
SIPA Electives | ||
| INAF U6016 | Cost-Benefit Analysis | 3.00 |
| INAF U6098 | Financial Risk Management and Public Policy | 3.00 |
| INAF U6301 | Corporate Finance | 3.00 |
| INAF U6326 | Renewable Energy Project Finance Modeling | 3.00 |
| INAF U6508 | Using Big Data to Develop Public Policy | 3.00 |
| INAF U6511 | Intro to Infographics and Data Visualization | 1.50 |
| INAF U6512 | Data Driven Approaches for Campaigns and Advocacy | 3.00 |
| INAF U6578 | Data Collection for Evaluation, Policy, and Management | 1.50 |
| INAF U6858 | Economics of US Social Policy | 1.50 |
| INAF U6889 | Impact Measurement ＆ Evaluation for Sustainable Development | 3.00 |
| INAF U6891 | Impact Evaluations in Practice | 1.50 |
| INAF U6892 | Monitoring and Evaluation: Driving Evidence-Based Development and Humanitarian Aid | 3.00 |
| INAF U8195 | Behavioral Development Economics | 3.00 |
Non-SIPA Courses | ||
| Courses offered at affiliate Columbia Schools. Please see Cross-Registration instructions to register. Courses not listed must be approved by the DAQA Director. Enrollment is not guaranteed. | ||
| ACTU K5841 | Data Science in Finance and Insurance | 3.00 |
| QMSS GR5073Q | Machine Learning for the Social Sciences | 3.00 |
| Code | Title | Points |
|---|---|---|
| Points | ||
Advanced Courses | ||
| INAF U6006 | Computing in Context | 3.00 |
| INAF U6503 | Applying Machine Learning | 3.00 |
| INAF U6506 | Data Science ＆ Public Policy | 3.00 |
| INAF U6514 | Text as Data | 3.00 |
| INAF U6600 | Testing Models of Public Policy Making | 3.00 |
| INAF U6614 | Data Analysis for Policy Research Using R | 3.00 |
| INAF U6659 | Advanced Computing for Policy | 3.00 |
| PUAF U8516 | Time Series Analysis | 3.00 |
SIPA Electives | ||
| INAF U6004 | Application Development for Social Impact | 1.50 |
| INAF U6005 | Generative AI | 1.50 |
| INAF U6009 | Artificial Intelligence in Public Policy | 1.50 |
| INAF U6098 | Financial Risk Management and Public Policy | 3.00 |
| INAF U6272 | Introduction to Data Analytics for Public Policy, Administration, and Management | 1.50 |
| INAF U6274 | Introduction to Database Design, Management, and Security | 1.50 |
| INAF U6275 | Geographic Information Systems and Analysis | 3.00 |
| INAF U6502 | Into to Text Analysis in Python | 3.00 |
| INAF U6504 | Python for Public Policy | 1.50 |
| INAF U6508 | Using Big Data to Develop Public Policy | 3.00 |
| INAF U6511 | Intro to Infographics and Data Visualization | 1.50 |
| INAF U6512 | Data Driven Approaches for Campaigns and Advocacy | 3.00 |
| INAF U6547 | Building AI Tools with Large Language Models | 1.50 |
| INAF U6548 | Artificial Intelligence Institutions | 3.00 |
| INAF U6576 | Data and Conflict | 3.00 |
| INAF U6593 | R for Public Policy | 1.50 |
| INAF U6892 | Monitoring and Evaluation: Driving Evidence-Based Development and Humanitarian Aid | 3.00 |
| INAF U6958 | Gender Data for Gender Equality | 1.50 |
Non-SIPA Courses | ||
| Courses offered at affiliate Columbia Schools. Please see Cross-Registration instructions to register. Courses not listed must be approved by the DAQA Director. Enrollment is not guaranteed. | ||
| ACTU K5841 | Data Science in Finance and Insurance | 3.00 |
| QMSS GR5073Q | Machine Learning for the Social Sciences | 3.00 |
Matriculated students in this program can view their degree audit report on Stellic.
For students interested in pursuing careers in data science to develop, implement, and assess public policies in both the public/nonprofit and private sectors, the Data Science for Policy (DSP) Concentration provides the opportunity to understand and apply computational and data analytics, econometrics and quantitative analysis to policy related issues.*
The Data Science for Policy (DSP) Concentration requires 15 credits, consisting of one required 3-point course, two courses (or 6 points) of Advanced Courses, and 6 points of electives.
*Please note only students who matriculated in Fall 2024 or later will be allowed to switch to the new concentration curriculum.
These prerequisites will be mandatory under the new MPA or quant-focused MIA programs, but current students are expected to have these courses fulfilled in order to concentrate in DSP.
| Code | Title | Points |
|---|---|---|
| Points | ||
| SIPA U6400 | Microeconomic Analysis for International and Public Affairs * | 3.00 |
| SIPA U6401 | Macroeconomic Analysis for International and Public Affairs | 3.00 |
| SIPA U6500 | Quantitative Analysis I for International and Public Affairs * | 3.00 |
| SIPA U6501 | Quantitative Analysis II for International and Public Affairs | 3.00 |
*Minimum grade requirement of B-.
| Code | Title | Points |
|---|---|---|
| Points | ||
| INAF U6006 | Computing in Context | 3.00 |
Select at least 6 points of courses to fulfill the requirements. Courses do not have to come from the same focus area, and Advanced Courses can count toward the Elective requirement.
| Code | Title | Points |
|---|---|---|
| Points | ||
| INAF U6503 | Applying Machine Learning | 3.00 |
| INAF U6599 | Quant III: Labor Economics For Policy Students | 3.00 |
| INAF U6600 | Testing Models of Public Policy Making | 3.00 |
| INAF U6604 | Applied Econometrics | 3.00 |
| INAF U6608 | Economics of Education Policy | 3.00 |
| INAF U6614 | Data Analysis for Policy Research Using R | 3.00 |
| INAF U8145 | Advanced Economic Development for International Affairs | 3.00 |
| INAF U8360 | Economic Measurement of Discrimination | 3.00 |
| SIPA U8500 | Quantitative Methods in Program Evaluation and Policy Research | 3.00 |
| PUAF U8516 | Time Series Analysis | 3.00 |
| Code | Title | Points |
|---|---|---|
| Points | ||
| INAF U6503 | Applying Machine Learning | 3.00 |
| INAF U6506 | Data Science ＆ Public Policy | 3.00 |
| INAF U6514 | Text as Data | 3.00 |
| INAF U6600 | Testing Models of Public Policy Making | 3.00 |
| INAF U6614 | Data Analysis for Policy Research Using R | 3.00 |
| INAF U6659 | Advanced Computing for Policy | 3.00 |
Select at least 6 points of courses to fulfill the requirements. Courses do not have to come from the same focus area
| Code | Title | Points |
|---|---|---|
| Points | ||
| INAF U6016 | Cost-Benefit Analysis | 3.00 |
| INAF U6098 | Financial Risk Management and Public Policy | 3.00 |
| INAF U6301 | Corporate Finance | 3.00 |
| INAF U6326 | Renewable Energy Project Finance Modeling | 3.00 |
| INAF U6508 | Using Big Data to Develop Public Policy | 3.00 |
| INAF U6511 | Intro to Infographics and Data Visualization | 1.50 |
| INAF U6512 | Data Driven Approaches for Campaigns and Advocacy | 3.00 |
| INAF U6858 | Economics of US Social Policy | 1.50 |
| INAF U6889 | Impact Measurement ＆ Evaluation for Sustainable Development | 3.00 |
| INAF U6891 | Impact Evaluations in Practice | 1.50 |
| INAF U6892 | Monitoring and Evaluation: Driving Evidence-Based Development and Humanitarian Aid | 3.00 |
| INAF U8195 | Behavioral Development Economics | 3.00 |
| Code | Title | Points |
|---|---|---|
| INAF U6004 | Application Development for Social Impact | |
| INAF U6005 | Generative AI | |
| INAF U6009 | Artificial Intelligence in Public Policy | |
| INAF U6098 | Financial Risk Management and Public Policy | |
| INAF U6272 | Introduction to Data Analytics for Public Policy, Administration, and Management | |
| INAF U6274 | Introduction to Database Design, Management, and Security | |
| INAF U6275 | Geographic Information Systems and Analysis | |
| INAF U6502 | Into to Text Analysis in Python | |
| INAF U6504 | Python for Public Policy | |
| INAF U6508 | Using Big Data to Develop Public Policy | |
| INAF U6511 | Intro to Infographics and Data Visualization | |
| INAF U6512 | Data Driven Approaches for Campaigns and Advocacy | |
| INAF U6547 | Building AI Tools with Large Language Models | |
| INAF U6576 | Data and Conflict | |
| INAF U6578 | Data Collection for Evaluation, Policy, and Management | |
| INAF U6593 | R for Public Policy | |
| INAF U6892 | Monitoring and Evaluation: Driving Evidence-Based Development and Humanitarian Aid | |
| INAF U6958 | Gender Data for Gender Equality |
Due to the MPA and quant-focused MIA requiring Quantitative Analysis II for International and Public Affairs (SIPA U6501) as a core course under the new curriculum, current students who switch to the new curriculum and wish to pursue a DSP minor will not be able to count SIPA U6501 for credit. Instead, students must take an additional 3 points of elective course(s) to fulfill specialization requirements for a total of 9 credits to fulfill the DSP minor:
For students switching to the non-quant-focused MIA curriculum, the DSP minor will maintain the same requirements as the current DAQA specialization.
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