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Introduction to Artificial Intelligence and Machine Learning

Artificial intelligence, machine learning and deep learning are topics of major importance to engineering practice. When used in one of their many implementations, new ideas for product design, factory operation efficiency, construction management, building operation and numerous other applications result. In this course the primary artificial intelligence methods (expert systems, genetic algorithms and neural networks) are described along with the associated data which must be available for their respective implementation. In addition the deep learning extension of neural networks is explored. Some of the many approaches to software implementation are demonstrated particularly those using Python. Computers are available for hands-on learning through provided examples of the algorithms and data.

Instructor

Dennis Miller

Dennis Miller

Dennis Miller has a BS and MS in electrical engineering with additional graduate work in computer science. He worked for 35 years for Johnson Controls, Inc. as an engineer and manager in building controls research, product development and software testing. ... read more

Benefits and Learning Outcomes

  • Gain insight into the primary approaches to AI and the types of engineering problems they can potentially be applied to
  • Experience machine learning, deep learning and some of the primary software tools available for implementation
  • Explore the importance of quality data to any AI process and some approaches to data analysis and modification for AI use

Date: Tue, Dec 1

Delivery Method: Live Online

Time: 8am-4:30pm CT

Platform: Zoom

Instructor: Dennis Miller

Fee: $595

CEUs: 0.7, PDHs: 7.0

Enrollment Limit: 40

Program Number: 4860-13213

Registration Deadline: Nov 28

Register Now

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