Data science is a broad field that harnesses many disciplines to derive insights and create value from data. The multi-disciplinary field involves mathematics, statistics, advanced algorithmic computing, data mining, artificial intelligence, machine learning, data engineering, data preparation, data visualization, and application of scientific method—all within the context of business domains to which it is applied. Through applied data science, organizations are able to predict and forecast, detect patterns and anomalies, make recommendations, optimize and automate processes, and much more. Data science allows analysts, decision makers and other business professionals to challenge assumptions, ask challenging questions, frame analytical opportunities, test hypothesis and deepen their understanding of how their customers, markets, assets and competitors behave.

The frequently used and often misunderstood term data scientist is not a one-size-fits-all role. Data science involves many personas including leaders and strategists, analytic modelers, statisticians, data analysts, and data engineers. The eLearningCurve curriculum for data science is designed to provide a foundation of fundamental concepts, cover the diverse needs of many data science personas, and continuously evolve with changes in this rapidly evolving field.