IEEE Academy on Artificial Intelligence

  • Course Program

Learn basic concepts in machine learning used throughout the course.  This learning path will provide surface-level knowledge on data, types of learning models, measuring efficiency, and optimizing machine learning.

Learning Path Length: 2.5 hours

Educator in Chief

Educator in Chief Phillip Sheu affiliated with University of California Irvine Samueli School of Engineering

Phillip Sheu

Dr. Phillip C.-Y. Sheu is currently a professor of EECS, Computer Science and Biomedical Engineering at the University of California, Irvine. He received his Ph.D. and M. S. degrees from the University of California at Berkeley in Electrical Engineering and Computer Science in 1986 and 1982, respectively. From 1986 to 1988, he was an assistant professor at School of Electrical Engineering, Purdue University. From 1989 to 1993, he was an associate professor of Electrical and Computer Engineering at Rutgers University.

A fellow of IEEE, Dr. Sheu currently is active in research related to semantic computing, robotic computing, artificial intelligence, biomedical computing and multimedia computing. He has published two books: Intelligent Robotic Planning Systems and Software Engineering and Environment - An Object-Oriented Perspective; and he is a co-editor of Semantic Computing (IEEE Press/Wiley). He also has published extensively in object-relational data and knowledge engineering. Sheu is the founder of the IEEE International Conferences of Semantic Computing (ICSC), Artificial Intelligence for Industries (ai4i), Transdisciplinary AI (TransAI), and the Computer Society Technical Committee on Semantic Computing (TCSEM). He is the founding editor-in-chief of the International Journal of Semantic Computing (IJSC) and is a co-founder of the IEEE International Conferences on Artificial Intelligence and Virtual Reality (AIVR), Multimedia Big Data (BigMM), Robotic Computing (IRC), and Artificial Intelligence and Knowledge Engineering (AIKE). He is also the inaugural educator-in-chief for the IEEE AI Academy.


Subject Matter Expert Joseph Barr affiliated with Acronis SCS

Joseph Barr

Dr. Joseph R. Barr is a data scientist practitioner and researcher. His experience in data analytics spans more than two decades. Joe is currently Vice President of Research at Acronis SCS. Over the past 25 years he has held leadership positions in several organizations and a few startup companies where he was instrumental in promoting artificial intelligence/machine learning and building related products. Joe holds a doctoral degree in mathematics from the University of New Mexico.

Subject Matter Expert Matthew Eng (Assistant) affiliated with University of CA

Matthew Eng

Matthew Eng is a developer studying computer science and artificial intelligence at the University of California, Irvine. He is working with Veryfi, a digital accounting company specializing in automated data extraction and document processing. Matthew has also produced similar tutorial and educational videos on programming. In the past, he has contributed to other open-source projects and specializes in web and software development.

For more information visit IEEE Academy webpage

Audience: The Academy is primarily for members who work in industry and need to understand new technical information quickly so they can apply it to their work. At the completion of the IEEE Academy on Artificial Intelligence, the learner will be able to demonstrate their new knowledge and will earn a certificate.

Publication Year: 2022

IEEE Academy on Artificial Intelligence
  • Course Provider: IEEE Academy
  • Course Number: ACADAI001
  • Credits: 0.25 CEU/ 2.5 PDH