Master AI with Deep Learning
About the Course
- Master the fundamentals of deep learning, from neural networks to advanced architectures like CNNs and RNNs, and learn how to apply these techniques to solve real-world problems.
- The learning experience is enhanced by several examples and problem sets that will be solved interactively during the lecture with the participation of the students.
- Many examples will be given throughout the lecture to reinforce the material learned.
- The course format includes 3 hours of daily lectures (2 hours of lecture and 1 hour of practical practice).
Course Level: Advanced
Fee: $$
About the Instructor
Dr. Alireza Sadeghian
Dr. Alireza Sadeghian has been with the Department of Computer Science at Toronto Metropolitan University since 1999, where he holds the position of the Professor. He is also an Affiliate Scientist at the Li Ka Shing Knowledge Institute, St. Michael's Hospital, and served as the research Theme Lead on Healthcare AI and Analytics at the Institute for Biomedical Engineering, Science, and Technology (iBEST).
Dr. Sadeghian was the Chair of the Department of Computer Science from 2005 to 2015. He is the founding Director of the Advanced Artificial Intelligence Initiative (AI2) Laboratory, Computational Intelligence Initiative (CI2) and Ubiquitous and Pervasive Computing Laboratories (UPCL), and has extensive expertise in the areas of AI, machine learning, Deep Learning, and modeling of complex dynamical systems particularly related to industrial and medical applications. He has supervised and trained 9 postdoctoral fellows, 8 PhD, and 24 Master’s students, as well as 60 research assistants. He has published over 150 journal manuscripts, refereed conference papers, and book chapters, as well as two edited books. He has also filed 2 invention disclosures and 2 patents.
Dr. Sadeghian has been actively involved with a number of international professional and academic boards, including IEEE Education Activity Board and NAFIPS board (North American Fuzzy Information Processing Society). Presently, he is the Chair of IEEE Computational Intelligence Technical Society Chapter, Toronto Section. Dr. Sadeghian is also on the Editorial Board of Applied Soft Computing Journal and serves as an Associate Editor of IEEE Access, Information Sciences, and Expert Systems Journal. He has served on over 80 conferences as Honorary Chair/General Chair/Organizer/Technical/Track Program Committee member, and has been a reviewer of many granting bodies including NSERC, MITACS, OCE, CFI, PRECARN, and PREA.
Alex Dela Cruz
Alex Dela Cruz is a Ph.D. in Computer Science focused on machine learning and its application in medical care at Toronto Metropolitan University. He is the recipient of several scholarships and awards, including the Queen Elizabeth II Graduate Scholarship in Science and Technology and the Ontario Graduate Scholarship. He is an active volunteer with IEEE Toronto, fulfilling a position as Computational Intelligence Society Vice-Chair and IEEE Toronto Student Activities Chair for 5+ years. Alex Dela Cruz has 15+ years of experience in software development and 10+ years of experience in AI, providing many AI seminars and workshops to researchers in the Greater Toronto Area.