Juana Sanchez & Shiqi Liang (UCLA)
Friday, May 20th 11-1pm; 1:30 - 3:30pm ET
Saturday, May 20th 11-1pm; 1:30 - 3:30pm ET
Most colleges in the United States offer time series training only at the graduate level, and they do so at a rather abstract, mathematical level. But the Volume, Velocity and Variety of time-stamped data produced and available nowadays, thanks to the IoT, smart cities, and sensors in general, and the enormous growth of data science as a profession have expanded the demand for time series analysis skills to less experienced learners and researchers. This workshop provides resources for teachers to train such learners and researchers to access, assess the quality of, clean, manage, describe, model and forecast time series data with classical and statistics time series methods and contemporary machine learning methods using R. The content of the workshop prepares beginners to know what it is that they are doing when they are asked to push buttons to forecast thousands of time series at their jobs.