New Course & Project! John Snow's Ghost Map & Forecasting Product Demand

Hi there, How can R be leveraged to predict demand for multiple products across a region? Conjointly, how can spatial analysis save the lives of many Londoners from a bacterial disease? Answer these questions and more in our new Project [Recreating John Snow's Ghost Map (Python)]( by Radovan Kavicky (President & Principal Data Scientist at GapData Institute) and new course [Forecasting Product Demand in R]( by Aric LaBarr (Director and Senior Scientist at Elder Research). [Recreating John Snow's Ghost Map (Python Project)]( In 1854, Dr. John Snow used a pre-computer method of spatial analysis to map cholera-induced deaths in London. He determined that a vast majority occurred around one particular water well. In this Python project, you will reanalyze the data and recreate John Snow's famous map, one of the earliest use of data visualization that saved many lives. You will test your data wrangling with pandas and interactive data visualization with Bokeh skills when completing this Project. [Forecasting Product Demand in R Course]( By knowing what things shape demand you can drive behaviors around your products, efficiently allocate resources, minimize inventory costs and more. It is a key contribution a data scientist can make to any business. This course will teach you how to identify important drivers of demand, look at seasonal effects, and predict demand for a hierarchy of products from a real-world example. Happy learning! DataCamp DataCamp Inc. | 350 Fifth Avenue | Suite 7730 | New York, NY 10118 | [Unsubscribe](