We offer credit and noncredit learning opportunities in a variety of subjects, from more traditional disciplines such as literature and philosophy, to business-oriented courses, to master’s degrees. Our courses are conveniently located in-person at the University of Chicago Gleacher Center and NBC Tower in downtown Chicago, and are primarily in the evening and on weekends, to fit the schedule of working adults. We also offer online courses, for those not located in Chicago, or who wish to study from home.
This course provides both a hands-on introduction and conceptual foundation for public health informatics.
This introductory course will present an overview of the basics concepts, techniques and algorithms used in Machine Learning.
This course will provide an introductory view of the breadth of healthcare delivery science covering a wide array of topics.
Exposure to basic statistical concepts that are necessary for students to understand the content presented in more advanced courses...
This course covers the analytics research process from the translation of business problems into researchable questions that can be addressed by using analytics...
Students learn how to work effectively in teams to identify, structure, and communicate the business value of data analytics to an organization.
This course will introduce students to the common algorithms: association and sequence rules discovery, memory-based reasoning, clustering, classification and regression decision trees, logistic models, and neural network models.
This course in advanced data mining will provide a practical, hands-on set of lectures surrounding modern predictive analytics and machine learning algorithms and techniques.
This course concentrates on the following topics: Review of statistical inference based on linear model, extension to the linear model by removing the assumption of Gaussian distribution for the output (Generalized Linear Model), extension to the linear model by allowing a correlation structure for the model residuals (mixed effect models), and
This course provides students with a thorough understanding of the fundamentals of data engineering platforms, for both operational and analytical use cases, while gaining expertise in building these platforms in a way to develop analytical solutions effectively.
The Data Science for Consulting course will enable students to understand the structure of consulting organizations and engagement, develop data science solutions to enterprise problems through employing traditional consulting frameworks and best practice tools and practice successful project delivery through effective data discovery, communicat
Review of financial markets and assets traded on them; main characteristics of financial analytics; concept of arbitrage; principles of volatility analyses; correlation, cointegration and other relationships between various financial assets; market risk analytics and management of portfolios of financial assets.
This course focuses on marketing analytics methods and applications that are used to develop marketing strategies, and create a link between marketing, customer behavior and business outcome.
This course will provide an overview of the development and rapid expansion of analytics in healthcare, major and emerging topical areas, and current issues related to research methods to improve human health.
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