This two-day course presented by the Columbia University Mailman School of Public Health will provide an introduction to the python programming language and demonstrate how it can be used to do essential data wrangling, manipulation and cleaning tasks using real-world biomedical data. Bringing together scalable methods and popular libraries for data manipulation, basic statistical analysis and visualization, this boot camp will provide participants with all the necessary tools and background for getting started with Python for data work. Through hosted notebooks, participants will leave the workshop with functioning code that they can then apply to their own data sets. Participants will receive orienting videos before the real-time sessions so they can familiarize themselves with the Jupyter Notebook/Google Colab environment; all code samples will be available in this format for participant use.
Investigators from any institution and from all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate.
No prior programming experience is required to participate in this workshop. However, participants must have (or create) an unrestricted Google account for working with sample notebooks (via Google Colab) and data sets. Likewise, participants will be expected to complete a brief survey and watch up to 3 hours of pre-recorded introductory material before the start of the real-time workshop activities.
Capacity is limited. Paid registration is required to attend.
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