This talk will focus on bringing pedagogical best practices into the data science classroom. We will begin by focusing on building confident coders, followed by an exploration of developing quantitative intuition, with a particular focus on understanding uncertainty. Finally, we will wrap up with tips for empowering strong data science communicators.
We are in an exciting new age with access to an overwhelming amount of data and information. This talk will focus on three areas that have become increasingly important as a result. First, we will discuss the importance of reproducibility during this age of information overload. As quantitatively minded people, we are being pushed to innovate and develop best practices for reproducibility. We will talk a bit about tools that make this possible and the next steps in this important area. We will then discuss new opportunities for developing innovative methods, particularly in the observational research space. This portion will include a brief introduction to causal inference for the data scientist. Finally, we will examine the importance of well-developed communication skills for quantitatively savvy people. These aspects will be discussed in the context of my winding path to data science, speckled with some advice and lessons learned.