University of Maryland

Data Literacy & Evidence Building

University Of Maryland | Coleridge Initiative


Join the community

A major goal of the class is to create a learning community and set of networks around specific datasets and real world agency problems. The class is set up to enable the impact of and learning from the class to continue well beyond the end of the training itself. After registering for the class, please create an account for Canvas, which you will need to be logged into for access to additional content and videos throughout the website. In order to help everyone get to know you, please provide a bio and headshot to the class discussion forum. Please summarize what you provided in your application material – what you hope to get out of the class, what your agency wants you to get out of the class, and a brief summary of your background (in three sentences or less).

Getting started: projects, products, practice

  1. Project: Meet with your team and develop a short summary of project goals. In addition, please answer the following sets of questions in this survey so that your team leads can target the team activities to the group interest.
  2. Product: Review the MultiState PostSecondary Report and consider how the report could be restructured to inform your agency’s needs
  3. Practice: If you have time, identify one of your agency stakeholders, fill them in on the class, and ask them to attend the final presentation

And yes, Python is named after Monty Python because it’s FUN

Review Python and SQL


As part of this class, you will be accessing data on Jupyter notebooks. If you have not used Jupyter notebooks before, here is the video on how to install Anaconda (10:51 minutes). Once you have everything set up, here is the short video on how to import and read data (14:55 minutes) so you can learn to pull in the required data to get start. Another key component participants should familiarize themselves with is exploring a DataFrame (19:05 minutes). It is likely that you will run into issues as you practice in your notebooks, so please watch the error message documentation video (7:12 minutes). We would like you to conclude your Python review by having participants learn data types (e.g. integer vs string) (15:58 minutes). If you are interested in further familiarizing yourself with Python, there are additional Python videos to review on Canvas.


We will introduce you to SQL, although it will not be a key focus area. We recommend brushing up on your SQL before we kick off the class starting with a video to introduce you to SQL (13:44 minutes). Our video tutorial will also help you learn the basics of SQL’s query language (14:08 minutes) and a frequently used joining function (9:52 minutes). Because we will use Python Jupyter notebooks in the class, it is necessary for you to explore how to integrate SQL into Python workflow (13:33 minutes). To gain basic knowledge about SQL functions in Python please gain understanding how to read SQL to Python (9:51 minutes) and understand SQL DataFrame in Python (11:31 minutes). If you’re a curious learner and want to discover more SQL functions, please find the additional SQL videos to watch on Canvas.

Please use the discussion forum to ask questions.

Make sure you know the basics before class

The class is customized for government agency staff who have to use data for decision-making in their day to day work.   We have found that one of the most difficult tasks is to scope a project, in other words to go from a high level “ask” to a concrete, evidencebased, answer.    We have created two sets of guiding for you to review that we hope can help: please click on the links below to access them.

  1. Project scoping and creating value
  2. Legal framework for accessing and using confidential data