TDC Applied Data Analytics Training FAQs
Q1: When will the TDC Applied Data Analytics Training be offered?
A1: The TDC will host "Applied Data Analytics Training" in Fall 2019, and again in early 2020. The fall course in-person sessions will occur September 18-20 and October 16-18. The timing for the early 2020 session is TBD and is anticipated to be filled with staff from TDC Pilot agencies.
Q2: How can I apply?
Q3: How much time will it take?
A3: The course involves a combination of in-person and online/remote-based work. The in-person commitment is 6 days (split into two three-day sessions), and between 30 -35 hours online/remote spread out before and after in-person sessions.
Q4: What are the dates?
A4: The in-person dates for the fall 2019 session are:
Module 1: September 18th - 20th
Module 2: October 16 - 18th
Q5: When does enrollment end?
A5: TANF agency staff will have priority registration through August 10th but enrollment is expected to close in mid-September.
Q6: Who directs the course?
A6: The program has three directors:
1) Julia Lane
Professor, Center for Urban Science and Progress and Wagner School
New York University
2) Frauke Kreuter
University of Maryland, University of Mannheim and IAB
3) Rayid Ghani
University of Chicago
Tuition and Scholarships
Q7: I'm not sure my employer has the funds for this. What kind of assistance do you offer? Who can receive that assistance?
A7: For the September 2019 course, TDC will pay for up to three attendees per site where the definition of “site” is driven by the TANF office that is applying to participate in the course (which could be a state, territory or county). The TDC will cover the cost of tuition and will provide financial support to cover associated travel costs (including airfare/train, accommodation, ground transportation and per diem) for up to three TANF agency staff to attend this course.
Q8: I'm from a TANF agency – how can I coordinate my travel to be paid for by TDC?
A8: TANF agency employees will automatically be considered for a full scholarship (up to three per agency) upon submission of application. TDC will get in touch with eligible participants to coordinate travel arrangements (including transportation to/from course, lodging, per diem, and ground transportation).
Q9: I've never coded before. Can I still participate?
A9: Yes! This course is built to support multiple interests and levels of technical experience whether you are a programmer or policy person. We've built in a pre-course for all attendees to become familiar with the programming tools used throughout the training (Python and SQL). This semi-structured pre-course of online introductory material starts 4 weeks prior to the in-person training and focuses on Python for the first 2 weeks and SQL for the latter 2 weeks.
Q10: Who can apply?
A10: TANF agency staff are the target audiences of this course. However, staff from other agencies, organizations or institutions (e.g., other government agencies, academic, private, or other) are also eligible to attend. TANF agency staff have priority registration through August 10th.
Q11: To which staff is the training geared towards?
A11: We invite people working with TANF data at all levels. For analysts and programmers, you will likely engage more thoroughly with the code, tools and technical components of the program. For non-programmers, you will become more informed about how these tools are used and will engage with the different types of methods available for data-driven decision-making.
Q12: How do people “collaborate” in the course?
A12: Collaboration occurs in-person during the training and online outside of the training via team calls and other tools such as Slack. You interact with your team outside of class to prepare a final presentation on your team project.
Q13: What reading materials guide the course?
A13: We use a free online textbook called Big Data and Social Science: A Practical Guide to Methods and Tools, which was edited by the creators of this course – Rayid Ghani, Frauke Kreuter, and Julia Lane - in collaboration with Ian Foster and Ron S. Jarmin. Go to: https://coleridge-initiative.github.io/big-data-and-social-science/ to access, but note that this edition is in the process of being updated.
"If you work in social science and would like to explore the power of big data, this book is clearly for you…This book is complete and comprehensive. It covers all necessary steps to finish a big data project; collecting raw data, cleaning and preprocessing data, applying various modeling tools to analyze the data, evaluating results, protecting privacy, and addressing ethical problems…All the important topics concerning big data are covered, making this book a good reference that you should always keep on your desk." (2017) Book Reviews, Journal of the American Statistical Association, 112:518, 878-882, DOI: 10.1080/01621459.2017.1325629
Q14: Can you provide examples of how I could apply what I learn when I'm back at my job?
A14. There are three primary ways that past participants have implemented learnings from the Applied Data Analytics program to their jobs: (1) in discussions with external service providers, course participants have been better able to both scope and define data projects or evaluate analyses performed by external partners; (2) communicating either the results of analyses or what is required of analyses to internal department stakeholders; and/or (3) leveraging the example analysis code from the program directly to perform an analysis.
Q15: What are example projects?
A15: Projects will use actual TANF data and focus on answering relevant questions like:
- What characteristics increase an individual's risk of returning to TANF?
- What are the employment outcomes of TANF leavers?
- What are the characteristics of those at-risk of not finding stable employment?
More detailed example project questions will be provided during the program and teams will have the opportunity to adjust their project in discussions with the program instructors.
Q16: How many staff per agency can attend?
A16: TDC will cover scholarships for up three participants per TANF agency and TANF staff have priority registration through August 10th. Beyond these parameters, and space permitting, there isn't a cap on total number of participants per agency.
What do people say about the course?
"... The Applied Data Analytics Training pioneers and disseminates new work efficiencies -- a set of behaviors with respect to a suite of new collaborative tools for working, sharing and documenting the work done with data and with coworkers, with data analysis and with project documentation… Presenting class activities which require interactive usage of these tools -- GIT, JUPYTER, ADRF and PYTHON – this training course has made me seriously reconsider the relatively unstructured current collaboration “model” by which most DataScientists muddle." - Salvatore Labaro, NYS Department of Health
"I am at the most awesome, intense, hands-on training for using data to improve public policy." - Noemi Reyes, Dane County Wisconsin
"I think this (ADRF Explorer) could be a VERY useful resource for a number of organizations." - Nolan Zaroff, City of Milwaukee / Dept. of City Development
"...I could see our agency benefiting from something like this, ... As the system builds out and collects additional resources/datasets that impact criminal justice system practices, this may be a place for us to look for the results of studies using evidence-based practices." - Katy Fitzgerald, Mecklenburg County Criminal Justice Services, North Carolina
"The breadth and depth of information that you have/will impart to participants is massive, a truly admirable goal. Your analogy of a buffet is apt as the supply of information seems without end." - George Putnam, Illinois Department of Employment Security
Please submit any additional questions you have to firstname.lastname@example.org.
 Slack is an online collaboration hub where people can easily connect; this will be available to you even after the course ends so that you can keep learning and connecting. See this website for more information about Slack: https://slack.com/