This course provides a broad overview of applied analytics frameworks and methods to help organizations turn data into informative insights. The chain of inferences leading from data collection to utilization for decision-making represents a comprehensive and coherent validation framework for the use of data to inform real-life problems. The course covers tools for addressing a set of claims about a problem based on data, such as exploratory data analysis, regression, causal inference, network analysis, and predictive analytics. It also introduces modern, computational methods in natural language processing and machine learning and how these methods are integrated and deployed within modern database frameworks to turn organizations in data-savvy organizations.
This course will help you recognize which applied analytic frameworks and methods to use to make smarter and better decisions and produce better results for your organizations. You will learn how different analytic methods are used to address critical data issues facing an organization and how best to apply those methods. You will learn how to conduct in-depth strategic analyses of business problems and communicate those results to all levels of an organization— to both technical and non-technical audiences. You will have the opportunity to apply these analytic methods to real problems in specific industries associated with your areas of interest.