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IIoT Series: Part 4: Machine Learning

One (1) Certified Professional Development Hour (PDH) available for all attendees.

 

Machine learning is a kind of artificial intelligence that uses statistical methods to let computers “learn” using data, without being explicitly programmed. However, machine learning is a synergistic exercise between man and machine, requiring human application of the scientific method and requiring communication skills, not to mention a vocabulary suited for collaboration with information technology departments and data scientists.

In this course, we’ll discuss the emerging machine learning paradigm for process control and enterprise management, as well as examine some real-life case examples that are already delivering results.


Learning objectives:

  • An overview of machine learning
  • Distinguish between supervised and unsupervised learning
  • Review machine learning case examples
  • Differentiate between Cloud and Edge applications

Course Instructors:
Allan Griffiths, principal consultant, Cambashi
Ed Kuzemchak, chief technology officer and director, embedded and IoT engineering, Software Design Solutions Inc.
Saif Ahmed, product owner, machine learning, Kinetica