Enrollment Options

TrendMiner MLHub Basic


 
This self-paced training provides a high-level overview of Machine Learning for Operations experts, and TrendMiner’s Machine Learning Hub (MLHub). First you will receive an overview of what you can expect from democratized machine learning and its value for an open-source community, in data collection, modelling, sourcing, dashboarding and reporting. This is followed by a short series of generic application demonstrations using TrendMiner’s MLHub and a short series of more specific operational applications. By the end of this course, you will be able to manage, understand and apply TrendMiner’s MLHub.

This course also allows you to earn a badge and be a Software AG Certified TrendMiner MLHub Associate. 

Learning Objectives

At the end of this course, learners will be able to:

  • Understand the wider applicability of machine learning in industrial operations
  • Navigate around TrendMiner's MLHub
  • Understand what MLHub can be used for
  • Understand how to apply MLHub

Software Versions Covered

  • TrendMiner (MLHub) version R2022.R1 onwards

Intended Audience

  • This course is intended for those starting out with TrendMiner’s MLHub
  • Process engineers, process operators, data analysts

Skills Pre-requisites

  • Basic understanding of data analytics
  • It would be beneficial to have access to the TrendMiner platform

Content Topics

  • Introducing TrendMiner’s MLHub
    • Open-source community
    • Data collection
    • Modelling
    • Sourcing
    • Dashboarding and reporting

  • Generic use case applications of MLHub
    • Soft Sensing
    • Predictive maintenance
    • Process Data Classification

  • Specific operational applications of MLHub
    • Water demand forecasting with Machine Learning
    • Anomaly Detection in the Performance of Energy Grids

Delivery Method

  • Basic courses are delivered as Self-Paced Course (pre-recorded Instructor presentations, product demonstrations, and hands-on exercises, as applicable)

Self-Paced Duration

  • Minimum of 85 minutes
Self-Paced Course Enrollment