Overview and Courses

Data is transforming how governments, researchers, and organizations understand complex social challenges and evaluate public policy. In this certificate program, you will learn how to apply data science techniques to analyze issues such as income inequality, educational opportunity, public health, and criminal justice, using data to better understand these challenges and inform policy decisions.

Throughout the program, you will use the R programming language and the RStudio development environment to analyze real-world datasets, perform statistical analyses, and create data visualizations that communicate meaningful insights. Along the way, you'll examine how data can be used to measure inequality, evaluate policy outcomes, and identify patterns across economic, demographic, and social issues.

By the end of the program, you will be prepared to analyze large public datasets, communicate findings through data visualization, and apply data-driven insights to support policy analysis and decision making.

To be successful in this program, you should have access to a New York Times subscription.

You will have six months to complete the program, with the flexibility to progress at your own pace and finish sooner if your schedule allows.

COURSE 1: Income Inequality and Intergenerational Mobility

This course introduces you to policy and data science surrounding income inequality and intergenerational mobility in the United States. You will begin with an in-depth background on sociology, demography, and economics, along with an introduction to “big data” and how it can be used in these fields of study to address complex policy problems. You’ll also explore essential functions in data science and the language of R before moving on to more complex statistics and data structures that will assist you in articulating big data.

You will then investigate income inequality utilizing the Opportunity Atlas data project to examine geographic differences in intergenerational income mobility. Finally, you’ll further study this mobility across race, ethnicity, and gender, and you’ll engage in several opportunities to practice your new skill set in R, data, and policy analysis.

COURSE 2: Impact of Racial-Ethnic Segregation on Education and Neighborhood Inequality

In this course, you will explore the data surrounding racial and ethnic inequalities in the United States, particularly in the areas of educational opportunity outcomes, residential segregation, and housing. You’ll examine visualizations of big data and practice analyzing this data to understand and convey its implications. You’ll not only investigate how these issues are defined but also how to measure different forms of inequality, articulate their cause, and utilize the data for informing policy.

You will explore the Educational Opportunity Project to develop your data analysis skill set by examining educational inequalities. You’ll then use R to visualize housing data and residential segregation. Finally, you’ll continue improving how your data is organized and shared by quantifying the social and economic impact of neighborhood housing and migration potential.

COURSE 3: Social and Economic Impact of the Early COVID-19 Pandemic

The COVID-19 pandemic upended our lives in fundamental and enduring ways, impacting not only our health but also the economy, culture, and politics. In this course, you will examine health inequalities and outcomes across different groups in the United States, utilizing the policies and effects of the COVID-19 pandemic as your framework. You’ll explore the impact of COVID-19 in such areas as employment, healthcare, energy use, patterns of movement, and consumer spending, and you’ll consider how policies implemented during the pandemic affected these variables for different groups in disparate ways. You’ll also examine remote data as well as a variety of spatial tools to help visualize the effect of pandemic-related policies.

By leveraging data, you will investigate how policies implemented during the pandemic affected health inequalities and outcomes for different groups in disparate ways across the United States, utilizing the policies and effects of the COVID-19 pandemic as your framework.

COURSE 4: Crime and Incarceration

In this course, you will investigate big data and policy analysis as it is applied to issues of crime, incarceration, and policing practices. Drawing upon an economic perspective, you’ll examine policymaking in the criminal justice system and how it affects crime rates and mass incarceration trends.

Incarceration has disproportionately impacted people of color in the United States, so you will also analyze trends of inequality in the United States criminal justice system and policing practices. Finally, you’ll explore how algorithms can be used with big data to inform policy and decision making, and you’ll practice building regression models to make predictions about crime rates.

AI Workshops All-Access Pass

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6-month subscription included

eCornell online Workshops are live, interactive 3-hour learning experiences led by Cornell faculty experts. These premium short-format sessions focus on AI topics and are designed for busy professionals who want to gain immediately applicable skills and strategic perspectives. Workshops include faculty presentations, breakout discussions, guided hands-on practice, and downloadable resources.

The AI Workshops All-Access Pass provides you with unlimited participation for 6 months from your date of purchase. Whether you choose to attend one workshop per month or several per week, the All-Access Pass will allow you to customize your AI journey and stay on top of the latest AI trends.

Hosted by Cornell faculty at the forefront of their fields, Workshops cover a range of cutting-edge AI topics applicable across industries. Whether you are just getting started with AI, seeking to build your AI skillset, or exploring advanced applications of AI, Workshops will provide you with an action-oriented learning experience for immediate application in your career. Sample Workshops include:

Work Smarter With AI Agents: Individual and Team Effectiveness
Leading AI Transformation: Bigger Than You Imagine, Harder Than You Expect
Using AI at Work: Practical Choices and Better Results
Search and Discoverability in the Era of AI
Don’t Just Prompt AI – Govern It
AI-Powered Product Manager
Leverage AI and Human Connection To Lead Through Uncertainty

How It Works

Format

Mentored Learning
All online

Time Commitment

96 hours with 6 months of access at your own pace

Engagement

100% self-paced

Power Your Career

Gain today’s most in-demand skills to stand apart.

Flexibility Fits Your Life

Learn on your schedule without stepping out of your job.

Personalized Facilitation

Receive expert feedback and guidance.

Real-world Projects

Apply learning and insights to your work to make an impact right away.

Learn From Top Minds

Courses are developed by Cornell faculty.

Format

Mentored Learning
All online

Time Commitment

96 hours with 6 months of access at your own pace

Engagement

100% self-paced

Power Your Career

Gain today’s most in-demand skills to stand apart.

Flexibility Fits Your Life

Learn on your schedule without stepping out of your job.

Personalized Facilitation

Receive expert feedback and guidance.

Real-world Projects

Apply learning and insights to your work to make an impact right away.

Learn From Top Minds

Courses are developed by Cornell faculty.

Faculty Authors

view details

Maria Fitzpatrick

Senior Associate Dean of Academic Affairs

Cornell Jeb E. Brooks School of Public Policy

Professor; Senior Associate Dean of Academic Affairs

Maria D. Fitzpatrick’s research focus is on child and family policy, with a particular interest in the economics of education. Specific studies have focused on early childhood education policies, higher education, teacher compensation, benefits and labor supply, teacher pensions and retirement, child maltreatment, incarceration’s effects on children and mothers, and the effects of retirement on the health of older Americans.

Professor Fitzpatrick is also Associate Dean of Academic Affairs in the Brooks School and Associate Vice Provost for Social Sciences in the Cornell Office of the Vice President for Research and Innovation. Professor Fitzpatrick is a Research Associate at the National Bureau of Economic Research, as well as an Affiliate in the CESifo Research Network, the Cornell Population Center, and the Center for the Study of Inequality.

Before arriving at Cornell, Professor Fitzpatrick was a Searle Freedom Trust postdoctoral fellow at the Institute for Economic Policy Research at Stanford University. After receiving an undergraduate degree at the University of North Carolina at Chapel Hill, she earned her Ph.D. in economics from the University of Virginia, where she was both an Institute for Education Sciences and Spencer Foundation Pre-Doctoral Fellow.

view details

Matthew Hall

Professor

Cornell Jeb E. Brooks School of Public Policy

Professor; Director, Cornell Population Center; and Director, MPA Program, Cornell Jeb E. Brooks School of Public Policy

Matt Hall is a demographer whose research focuses on immigration, racial/ethnic inequality, population change, and demographic methods. He has contributed to research assessing the economic and social impacts of unauthorized migration, the emergence of Latino boom towns and other new immigrant destination areas, and the changing nature of racial stratification and segregation in housing and neighborhoods.

Professor Hall’s current research projects focus on understanding the consequences of intensified interior immigration enforcement, the link between immigration status and child development, describing patterns of racial discrimination in U.S. housing markets, and the development of data science tools for demographic estimation.

Professor Hall is Director of the Cornell Population Center (CPC), Director of the Program on Applied Demographics (PAD), and Director of the MPA Program. He received his undergraduate degree from Western Washington University and his Master’s degree and Ph.D. from The Pennsylvania State University.

Key Course Takeaways

Examine how data is used to compare income inequality and intergenerational mobility across race, ethnicity, gender, and geography
Analyze and visualize data to determine the impact of racial-ethnic segregation on education and neighborhood inequality
Use regression techniques to analyze the relationships among variables to measure the social and economic impacts of the COVID-19 pandemic and the effectiveness of government policies during this time period
Examine trends in crime and incarceration that inform criminal justice policy and analyze this data with statistical models that reduce bias

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“

I like to think outside of the box, and this program from eCornell helped me conceptualize how I want to approach data problems going forward. I was able to actually apply new course concepts to my work, rather than simply repeat steps with different values.

‐ Mark T.

What You'll Earn

Big Data for Policy Certificate from Cornell’s Jeb E. Brooks School of Public Policy
96 Professional Development Hours (9.6 CEUs)

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Who Should Enroll

Aspiring data scientists and data analysts interested in public policy and social impact
Policy analysts and public sector professionals who use data to inform decisions and evaluate outcomes
Program evaluators, researchers, and social scientists seeking to strengthen their data analysis skills
City, regional, and community planners who rely on data to guide planning and policy decisions
Business and financial analysts interested in applying data science techniques to public policy and social challenges

Big Data for PolicyCornell Certificate Program

Overview and Courses

How It Works

Faculty Authors

Key Course Takeaways

Download a Brochure

What You'll Earn

Watch the Video

Who Should Enroll

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