Events

Summer 2023 dates: In-person at Columbia Mailman School of Public Health July 24-25, 2023; 9:00am - ~5:00pm ET   The Python Data Wrangling Boot Camp is a two-day intensive course that combines concept-focused seminars with hands-on exercises pairing Python fundamentals with practical data wrangling and analysis. This two-day course 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. By the end of the workshop, participants will be able to: Load and explore data sets in Python Join, reconcile and otherwise clean up messy data sets Do basic statistical analyses, including linear and logistic regression Render exploratory visualizations Audience and Requirements 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. Instructor Training Director: Susan McGregor, Associate Research Scholar, Columbia University Data Science Institute (DSI).  Additional Information View the training website for more details. Subscribe for updates on new Python Data Wrangling Boot Camp details and registration deadlines. Contact the Python Data Wrangling Boot Camp team. Capacity is limited. Paid registration is required to attend.

Summer 2023 dates: In-person at Columbia Mailman School of Public Health July 24-25, 2023; 9:00am - ~5:00pm ET   The Python Data Wrangling Boot Camp is a two-day intensive course that combines concept-focused seminars with hands-on exercises pairing Python fundamentals with practical data wrangling and analysis. This two-day course 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. By the end of the workshop, participants will be able to: Load and explore data sets in Python Join, reconcile and otherwise clean up messy data sets Do basic statistical analyses, including linear and logistic regression Render exploratory visualizations Audience and Requirements 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. Instructor Training Director: Susan McGregor, Associate Research Scholar, Columbia University Data Science Institute (DSI).  Additional Information View the training website for more details. Subscribe for updates on new Python Data Wrangling Boot Camp details and registration deadlines. Contact the Python Data Wrangling Boot Camp team. Capacity is limited. Paid registration is required to attend.

Summer 2023 dates: In-person training July 26-27, 2023 9:00am - ~5:00pm EDT The Environmental Mixtures Workshop is a two-day intensive training of seminars and hands-on analytical sessions to provide an overview of environmental mixtures concepts, techniques, and data analysis methods used in health studies. This two-day intensive workshop will provide a rigorous introduction to multiple different techniques to analyze exposure to mixtures in environmental health. Led by a team of world experts in environmental health, epidemiology and statistics, many of whom have developed their own methods to analyze exposure to mixtures, the workshop will integrate seminar lectures with hands-on computer lab sessions to put concepts into practice. Emphasis will be given to supervised and unsupervised methods. Since the choice of method depends on the research question at hand, the workshop will conclude with a panel discussion on when each method presented is appropriate for use and for which research questions.   By the end of the workshop, participants will be familiar with the following topics:  Principal Component Analysis (PCA)  Factor Analysis (FA)  Clustering  Variable Selection (Lasso, elastic net)  Bayesian Kernel (BKMR)  Weighted Quantile Sum Regression (WQS)  Emerging mixtures topics and novel extensions  Tree-based methods  AUDIENCE AND REQUIREMENTS Investigators at all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate. There are four requirements to attend this workshop: Each participant must have an introductory background in statistics. Each participant must be familiar with R. Each participant is required to have a personal laptop/computer and a free, basic RStudio Cloud account.  All lab sessions will be done using RStudio Cloud. Per Columbia University Policy, on-campus participants must be vaccinated and should be prepared to show proof of vaccination while on campus. Any changes to on-campus policies will be updated here and communicated to participants. ADDITIONAL INFORMATION View the training website for more details. Subscribe for updates on new Boot Camp details and registration deadlines. Contact the Boot Camp team.  

Columbia Health* is offering virtual Naloxone training on Fri. Jul 28, 12 - 1 PM ET. Register on Zoom. *Columbia Health is a Registered Opioid Overdose Prevention Program, recognized by New York City and State Departments of Health. This designation came as part of a collaboration with researchers from the Mailman School of Public Health and the School of General Studies. Learn more about our Opioid Education and Naloxone Training program on our website.  Columbia University makes every effort to accommodate individuals with disabilities. If you require closed captioning, sign-language interpretation, or any other accommodation, please contact Disability Services at (212) 854-2388 or disability@columbia.edu at least 10 days in advance.