Gain rigorous data analytical skills with a unique focus on policy impact and specialized track for academic or professional growth in 7 weeks.
Request Info Attend an Event Download the BrochureData is everywhere and analytical skills are in high demand by public and private institutions around the world. Over seven weeks, you will gain the skills to retrieve, analyze, and present data through a public policy lens. Learn to use a scientific approach to address today's social issues and create a measurable impact on society.
Data Analytics, R Programming, Public Policy, Policy Research
All levels welcome
Seven (7) weeks, 10-15 hours per week
June 10 - July 26, 2024
$4,500 with partial scholarship available
Austin WrightAssistant Professor at the Harris School of Public Policy
“The DPSS program was a critical first step. Being out of an academic environment for almost a decade, I wanted to prepare for this rigorous curriculum. While DPSS was challenging, I had an extremely supportive community of classmates, TAs, and professors. DPSS was the tipping point that made Harris my number one choice.”
DPSS’22, MPP Class of 2025
“It’s a summer I won’t forget. The quantity and quality of learning kept me engaged, and the other scholars were such a joy to work with. There were people from all walks of life, which was very reflective of the real world. I was among the youngest, so I was mindful of that as I went through it. But after each session, I felt more and more confident and encouraged to engage with my classmates, faculty, and staff.”
“In the short-term, I wanted to apply the quantitative skills I gained from DPSS to better analyze cyber conflict in the context of the Department of Defense Cyber Strategy of Defending Forward. Long-term, I hoped my exposure to policy practitioners and UChicago faculty would prepare me for graduate study.”
DPSS’21, MPP Class of 2024
DPSS equips you with training in data analytics paired with hands-on policy research experience and professional development resources. The program includes three required modules: (1) Data Analytics in Public Policy; (2) Introduction to R Programming; and (3) an immersive Capstone Research Project.
Depending on your primary learning goal, participants can opt for one of the two tracks - the academic track and the professional track. Both tracks provide core foundational courses accompanied by a diverse array of customized resources, ensuring you are ready for your next steps - whether it be getting ready for top-notch graduate programs or preparing for a career pivot.
This course provides an introduction to the statistical foundations, tools, and methods employed by public policy researchers. Explore the fundamental problem of causal inference and learn how to use data, research design, and statistical modeling to navigate around this problem.
This is an introductory course in programming and data analysis for students with no prior coding experience. It begins with foundational basics and progresses to advanced, practical data analytical and visualization skills in R. By the end of the course, you will be able to use R to retrieve, clean and analyze complicated datasets and produce tables, charts and other data visualization tools to convey your findings.
In the capstone research project, you will collaborate with faculty and a group of peers to tackle a real-world issue with datasets, devising solutions and creating deliverables that can enhance your portfolio online.
Academic track participants will harness the skills of research design, policy analysis, and team collaboration to conduct a research project using open-source or faculty-provided datasets. Participants will individually write a research note, showcasing their academic readiness for graduate programs or research jobs.
Professional track participants will dive into real-world datasets with practical analysis and a focus on data visualization. They will produce a policy memo with data visualization (charts, infographics) and get the chance to explore Github to showcase their results online.
The academic track provides a comprehensive toolkit for participants who are interested in further advancing their academic growth by earning a master or PhD-level degree in the social sciences field. Students undertaking this track are required to complete advanced statistics and programming learning such as panel data designs, regression discontinuity, instrument variables etc. of the Data Analytics and Programming in R courses, fostering a comprehensive understanding of advanced content. In addition, as part of the Module 3 Capstone Project, participants will individually write a research note that can be used as a writing sample for one's graduate degree application. Participants will also join live workshops focusing on understanding the academic world and learn tools such as LaTeX to support their future research journey.
The professional track prioritizes applied data analytical skills and techniques of data visualization and storytelling, allowing participants to maximize the application of data analysis in real-world professional settings. In this track, participants only need to complete a portion of the assignments of the Data Analytics and Programming in R courses (Module 1 & 2), providing greater flexibility in their time management. Participants will use the Capstone Project as an immersive learning experience to conduct data storytelling and data visualization practice , and produce a policy memo as a deliverable. In addition, participants will join live workshops focusing on understanding how data skills can be applied in various types of industry jobs, and explore useful resources such as GitHub and QGIS to build the online presence to signal their skillset to future employers.
Sun | Mon | Tue | Wed | Thu | Fri | Sat |
Weeks 1 - 5 | Break | Optional: Live Office Hours | Break | Optional: Live Office Hours | ||
Module 1: Data Analytics in Public Policy | Optional: Take Non-Graded Quizzes | Module 1: Data Analytics in Public Policy | ||||
Module 2: Introduction to Programming in R | Module 2: Introduction to Programming in R | |||||
Optional: Community Events | Homework in Progress | Optional: Community Events | Finish Homework |
Sun | Mon | Tue | Wed | Thu | Fri | Sat |
Weeks 6 - 7 | Break | Optional: Live Office Hours | Break | Break | ||
Module 3: Capstone Research Project | ||||||
Optional: Community Events |