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This course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment. Students will learn about each phase of the pipeline from instructor presentations and demonstrations and then apply that knowledge to complete a project solving one of three business problems: fraud detection, recommendation engines, or flight delays. By the end of the course, students will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that solves their selected business problem.

Teaches data engineers how to run DataStage jobs in a Hadoop environment. You will run jobs in traditional and YARN mode, access HDFS files and Hive tables using different file formats and connector stages.

IBM Stewardship Center for Information Server v11.5 provides event notification with workflow and remediation.