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Self-Paced E-learning course: Advanced Analytics in a Big Data World


The course covers the entire analytics process, from data preprocessing to advanced modeling, including ensemble methods (bagging, boosting, random forests), neural networks, SVMs, Bayesian networks, social networks, monitoring and more.



Baesens Analytics Big Data World
Self-Paced E-learning course: Advanced Analytics in a Big Data World


The E-learning course starts by refreshing the basic concepts of the analytics process model: data preprocessing, analytics and post processing. We then discuss decision trees and ensemble methods (bagging, boosting, random forests), neural networks, support vector machines (SVMs), Bayesian networks, survival analysis, social networks, monitoring and backtesting analytical models.

Throughout the course, we extensively refer to our industry and research experience. Various business examples (e.g. credit scoring, churn prediction, fraud detection, customer segmentation, etc.) and small case studies are also included for further clarification.

The E-learning course consists of more than 20 hours of movies, each 5 minutes on average. Quizzes are included to facilitate the understanding of the material. Upon registration, you will get an access code which gives you unlimited access to all course material (movies, quizzes, scripts, ...) during 1 year. The E-learning course focuses on the concepts and modeling methodologies and not on the SAS software. To access the course material, you only need a laptop, iPad, iPhone with a web browser. No SAS software is needed.

The course is taught by Prof. Bart Baesens, a leading researcher on data mining and its applications.

See support.sas.com/edu/schedules.html?id=2169&ctry=US for more details and to register.

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