A Hands-On Introduction to Artificial Intelligence: How Machines Learn

Artificial Intelligence (AI) powers many of the technologies we use every day, from smartphones to self-driving cars. But how do machines actually learn? In this interactive workshop, participants will explore the fundamentals of machine learning by building a simple AI system using a single-board computer and an accelerometer sensor. They will collect motion data, train an AI model to recognize different movement patterns, and test their system in real time. Through hands-on experimentation and guided coding activities, participants will gain practical experience with sensors, data collection, machine learning, and embedded systems while discovering how intelligent systems are created.

Dr. Farhang Sahba, P.Eng. 

Farhang is a professor of Electrical and Computer Engineering at Sheridan College. He received his BSc in Electrical Engineering from Isfahan University of Technology, his MSc in Electrical Engineering from Toosi University of Technology, and his PhD in Image and Signal Processing from the University of Waterloo.

Farhang followed his education with a postdoctoral fellowship at University of Toronto, and Ryerson University’s Signal and Information Processing Lab, where he conducted a number of research projects in the fields of image and signal processing, machine learning, and fuzzy systems.

Prior to joining Sheridan, Farhang was a senior research engineer with Merge Healthcare working on the design and implementation of a computer-aided diagnosis engineering platform for magnetic resonance imaging systems. He also worked as a research scientist with Segasist Technologies, where he carried out research on an innovative intelligent segmentation technology for image analysis systems.

Farhang was part of the committee responsible for the development of Sheridan’s Electrical Engineering Bachelor’s Degree program. In addition, he has worked as the technical lead for several applied research projects in Sheridan’s School of Mechanical and Electrical Engineering Technology. His main research areas are artificial intelligence, machine learning, computer vision, and IoT-based 5G networks.

Farhang is a member of the Professional Engineers Ontario (PEO) and a senior member of the Institute of Electrical and Electronics Engineers (IEEE). In addition, he is a member of the IEEE Computational Intelligence Society, IEEE Robotics and Automation Society, and IEEE Signal Processing Society. He has acted as a reviewer for several conferences and journals and has more than 40 papers published in various journals, conferences, book chapters, and technical reports.

Dr. Hooman Nabovati, P.Eng.

Hooman Nabovati is a registered Professional Engineer in the Province of Ontario. He received his Ph.D. in Electrical Engineering in 2006.

Hooman’s teaching experience includes courses on analog and digital circuits, electrical motors, communication systems and circuits, electronic fabrication, and semiconductor devices. Hooman is committed to teaching excellence and is always looking to bring effective teaching strategies to the classroom. He is dedicated to providing a positive learning environment for all students.

Hooman has been working with multiple industry partners on design, manufacturing, and testing of digital telecommunication systems, data acquisition and instrumentation, RFID systems, and measurement instruments.

Hooman is a member of Professional Engineers Ontario (PEO) and Institute of Electrical and Electronics Engineers (IEEE) and has published more than 40 papers in scientific journals and international conferences.