Introduces students to predictive analytics techniques and their application in business decision-making. Students learn to leverage historical data to predict future outcomes using programming languages utilizing machine learning models such as linear regression, decision trees, cluster analysis and time series forecasting. Students are required to design, build and implement predictive models for real-world datasets that can affect business strategy.

Introduces students to prescriptive analytics techniques and their applications to recommend an optimal course of action in uncertain environments. Students learn how to solve complex business problems such as pricing strategy, financial risk, and energy consumption using optimization, simulation, heuristics and advanced analytical techniques to recommend optimal actions to take to mitigate risk and achieve desired outcomes.

S/U grade assessment.

Addresses the unstructured data management skills needed for modern data analysis including those salient to big data and real-time data environments. Introduces unstructured data, including both well-formatted data (XML, JSON etc.) and free flowing information. Learn about software and databases as well as methods for identification, acquisition, extraction, validation/cleansing, representation and analysis of data for organizational use. Learn how to store and manipulate unstructured data, how to mine text and how to manipulate and analyze unstructured data to enable better decision-making. Briefly introduces data visualization tools as a way to communicate effectively insights gained from analyzing unstructured data.

Takes insights derived from the analytics and focusses on how to communicate these actionable insights to executives for decision-making purposes. Includes presentation and storytelling skills, and the ability to communicate to both technical and managerial audiences. Students also need to be able to measure the outcomes based on the decisions that were made with the data-storytelling. Looks to develop good listening and team building and other communication skills.

Lectures and discussions in an area which, because of its topicality, is not the subject of a regular course. Topics are designated in the Schedule of Classes.

S/U grade assessment.

S/U grade assessment.