The booming demand for skilled data scientists across industries makes this course particularly suited for the following professionals:
You will be working on 4 real-life industry based projects spread over 4 domains
Healthcare : In healthcare and other industries, predictors are most useful when their knowledge can be transferred into action. The willingness to intervene is the golden key to harnessing the power of historical and real-time data. More importantly, to best judge the efficacy and value of forecasting a trend and ultimately changing behavior, both the predictor and the intervention must be integrated back into the same system and workflow where the trend originally occurred. Predictive analytics can also be used in healthcare to mediate hospital readmissions.
Insurance : Predictive analytics use has increased greatly in insurance businesses, especially for the biggest companies, according to the 2013 Insurance Predictive Modeling Survey. While the survey showed an increase in predictive modeling throughout the industry, all respondents from companies that write over $1 billion in personal insurance employ predictive modeling compared to 69% of companies with less than that amount of premium.
Retail : Optimizing product placements on shelves or optimization of inventory to be kept in the warehouses using industry examples. Through this project, participants learn the daily cycle of product optimization from the shelves to the warehouse. This gives them an insight of the regular happenings in the retail sector.
Internet : Internet analytics is the collection, modeling, and analysis of user data in large-scale online services, such as social networking, e-commerce, search, and advertisement. In this class, we explore a number of key functions of such online services that have become ubiquitous over the last couple of years. Specifically, we look at social & information networks, recommender systems, clustering and community detection, dimensionality reduction, stream computing, and online ad auctions.