Computational Social Science
Online Certificate Program
Study with a Nobel Laureate… from wherever you are. Learn cutting-edge social science skills, statistical techniques and technologies.
Today’s social scientists must work with massive datasets of unprecedented complexity, process vast amounts of information and create sophisticated computer models and simulations. Whether your interest lies in economics, politics, sociology, psychology, or in another discipline, our online certificate program can help you harness the power to make original and lasting contributions in the social sciences.
Whether you’re just starting out or want to get to the next level, we have what you need.
Designed by a Nobel Laureate
This four-course online certificate program is overseen by New York University economist Thomas J. Sargent, who was awarded a Nobel Prize in 2011. Unlike at many major universities, where courses are often taught by graduate assistants, in this program you’ll be taught by Dr. Sargent along with his handpicked team comprising former students Chase Coleman and Spencer Lyon. They co-designed the program with Dr. Sargent and are lead developers at QuantEcon, an organization that provides open source computational tools for social scientists.
Why Get a Certificate?
The NYU Computational Social Science online certificate program prepares students for either a graduate program in the social sciences or for a career as a data analyst or computational social scientist. Computational social scientists work throughout the public and private sector – at universities, private research institutions and business enterprises such as tech companies like Amazon, Apple, Facebook, Google, and Uber.
What Can You Do With These Skills and Tools?
With access to a dizzying array of social data generated by user interactions on digital devices and platforms, you could analyze online social interactions, chart consumer purchases and credit card transactions, explore income disparity, illuminate race- and gender-based discrimination, or track the higher infectious rates in disadvantaged communities. You could tap into this immense datastream to shed light on the spread of fake news and information, illustrate the shortcomings of facial recognition technologies, or sift through billions of text messages to figure out if there are truly six degrees of separation between people. You could code bots to burrow into social media chatter to figure out what people are really saying and thinking, study the behavior of online trolls, or measure the impact of advertising on consumers. And when you’re done, you can program predictive models to forecast likely future outcomes.
Course Sequence
Dr. Sargent, Dr. Coleman, and Dr. Lyon jointly teach all four courses in the sequence, as well as a required self-paced 12-week summer “pre-class” that introduces you to the Python programming language and elementary software engineering tools. In the fall, you take courses on mathematical foundations and data tools in the social sciences. In the following spring your classes cover dynamic models and machine learning. Each course builds on the preceding course to provide you with the foundations you’ll need to succeed in your chosen academic and/or career path. The only prerequisites are working knowledge of linear algebra and calculus: derivatives.
Courses
Online Foundations
An online, self-paced course to introduce students to Python and elementary software engineering tools.
Mathematical Foundations for Computational Social Science
Review essential math and dive deeper into random variables, model building, and model estimation (both frequentist and Bayesian).
Data Tools for Computational Social Science
Arm yourself with cutting-edge data manipulation and management tools and use them on real-world “messy” data sets.
Dynamic Models for Computational Social Science
Learn dynamic programming, time-series analysis, Markov models, Hidden Markov Models and text analysis. Apply these tools to academic, government and industry research.
Machine Learning for Computational Social Science
Apply classical and cutting-edge machine learning techniques to real-world problems in the social sciences.
Faculty
Thomas Sargent
Dr. Thomas Sargent is co-founder and co-author of the QuantEcon website and past president of the American Economic Association, the Econometric Society, and the Society for Economic Dynamics. He has written several textbooks on macroeconomics and time series analysis. He loves Python and machine learning and teaching. With his good friend, Christopher Sims, he shared the Nobel prize for Economic Sciences in 2011.
Chase Coleman
Dr. Chase Coleman is a managing director at Valorum Data, a co-author of the QuantEcon Data Science lectures, and he helped build the data engineering team at CovidActNow. Chase received his PhD in economics from NYU Stern School of Business in 2019. While at Stern, he co-developed the “Data Bootcamp” course and has taught similar courses and workshops around the world. He loves mathematics, economics, and programming, and he compulsively buys books on all three topics.
Spencer Lyon
Spencer Lyon is an economist (PhD NYU Stern, 2018) actively involved in various roles at the intersection of economics, data science, and computer science. Spencer currently serves as managing director of Valorum Data and co-leads the data engineering team at CovidActNow. Spencer is co-author of the QuantEcon Data Science lectures, co-creator of NYU Stern’s “Data Bootcamp” course, primary lecturer and organizer for the ML and big data seminar series for the MS Data Analytics program at the University of Central Florida, and instructor in various graduate-level training engagements on applied deep learning for Fortune 100 companies.
Request more info
If you have further questions about the computational social science online certificate program, please contact Dr. Tom Sargent (thomas.sargent@nyu.edu) for academic queries or program administrator (css-admin@nyu.edu) for administrative questions.
Frequently Asked Questions
The program consists of four 3-credit graduate courses. You can look up the latest information regarding tuition and fees by academic year on the NYU Bursar’s Website. As of Fall 2021, a 3-credit course in the Graduate School of Arts and Sciences is $6,671 USD.
As an online student you won’t have to move to New York, no need for a visa for international students, and you can continue to work while completing your certificate.
The program consists of one self-study pre-course before the certificate begins, followed by four 3-credit graduate courses.
The certificate will take two semesters to complete. You’ll take two courses the first semester and two courses the second semester. The courses are taken sequentially as you’ll use skills learned in the first semester to successfully complete your second semester.
No exams are required to apply for this certificate.
The certificate is fully online and does not meet in-person.
Completion of the certificate will prepare students for further graduate studies, but does not guarantee admission to NYU’s graduate programs. All students are encouraged to apply for the graduate program of their choice if they wish to pursue further studies.
You will need access to a computer operating Windows, Mac, or Linux.
No formal experience is required. You’ll gain the necessary foundation for success in the pre-certificate self-study course.
No language exams are required for this certificate.
There are many job opportunities for competent Python programs who are literate in social science research tools. Jobs are available in big tech companies, government and international agencies, financial institutions and more. The certificate will also prepare students to pursue further graduate studies.
Yes, students can complete the certificate while working. Students should plan to spend an average of 20 hours per week on coursework.
If you have questions, please contact Program Administrator Lydia Page at lydia.page@nyu.edu.