This course will help you prepare for the certification exam and the exam fee is waived with this course.
The Aspen Mtell application is a condition monitoring solution that uses automated Machine Learning to stop machines from breaking down, makes them last longer, reduces maintenance costs, and increases the net product output of any process.
In this training, users build and deploy Machine Learning Agents on few selected Critical Assets following best practices during the training session. During the training users will build Asset Hierarchy, Import Equipment Set, Import TDS, Audit Sensors data, clean and update the Equipment set, Deploy Hidden Failure Agents, Anomaly Agents, and Failure Agents. Review Anomaly Agents and Failure Agents. Review active alerts and Agent retuning. Transfer learning on similar Assets. Practice automatic Agent tuning for the best accuracy and earliest detection of excursions from normal behavior, and the precise patterns that match degrading conditions that lead to failure.
Build agents using your own data. Clean, prepare, and organize data for agent building. Learn advanced Agent building techniques such as transfer learning. Evaluate and retune live Agents based on changing process conditions.
Some knowledge of Aspen Mtell Prescriptive Maintenance concepts is expected. Prior completion of the MPM101 or MPM121 Learn to build Machine Learning Agents using Aspen Mtell Course will greatly enhance the value of this course.
To Build Machine Learning Agents on Critical Equipment, it's essential to complete the below prerequisites prior to the class.
Aspen Technology, Inc. awards Continuing Education Units (CEUs) for training classes conducted by our organization. One CEU is granted for every 10 hours of class participation.