WHEN
4 - 7 OCTOBER 2021
WHERE
MS TEAMS
TIME
2.00PM - 5.30PM
RM 950 FOR PROFESSIONALS
10% Discount for Early Bird (until 4 September 2021) / Group / Students
COURSE SUMMARY
INTRODUCTION
Traditional machine learning techniques have been commonly used in various applications. Over the last few years, many researchers have shifted from traditional machine learning to deep learning techniques due to their promising applications. The course will start with an overview of traditional machine learning techniques. It will then introduce the basic principles of deep neural and convolutional neural networks (CNN) along with some of the well-known architectures that have been developed. Examples of deep learning applications from various fields will be presented. To conclude some challenges and directions will be highlighted.
WHO SHOULD JOIN US TO :
OBJECTIVES
Upon completion of this course, participants will be able to:
Apply Deep learning techniques.
1. Associate Professor Dr Ibrahima Faye
Dr Germain Forestier current position as Professor at the University of Haute-Alsace (France). Research interests: Data science, data mining, time series, machine learning, big data, artificial intelligence and deep learning. Germain Forestier received his PhD in Computer Science from the University of Strasbourg in 2010. He then spent one year as a postdoctoral fellow at INRIA Rennes / INSERM (French National Institute for Medical and Health Research), where he worked on biomedical data analysis. In September 2011, he obtained a position of Associate Professor at the University of Haute-Alsace (France) and is now Professor since 2018. Prof. Forestier also hold a position of Associate Professor (Adjunct) at the Monash University (Australia). His research interests include data science, data mining, time series, machine learning, big data, artificial intelligence and deep learning. More info: https://germain-forestier.info/
3. Professor Dr Fabrice Meriaudeau
Dr Fabrice Meriaudeau current position as Professor at the Université de Bourgogne- France. Research interests: image processing for non-conventional imaging systems (UV, IR, polarization) and medical/biomedical imaging. Fabrice Meriaudeau was born on March 18, 1971, Villeurbanne. He received both the master degree in physics at Dijon University, France as well as an Engineering Degree (FIRST) in material sciences in 1994. He also obtained a Ph.D. in image processing at the same University in 1997. He was a postdoc for a year at The Oak Ridge National Laboratory. He was the director of the Institute Health and Analyt ics (2017/2018) at the Universiti Teknologi PETRONAS Malaysia and was the Director of the Le2i (UMR CNRS), Université de Bourgogne - France, which had more than 200 staff members, from 2011 to 2016. He is now with ImVia research group at the Université de Bourgogne- France and leads the Artificial Intelligence research group. He coordinated an Erasmus Mundus Master in the field of Computer Vision and Robotics from 2006 to 2010 and was the Vice President for International Affairs for the University of Burgundy from 2010 to 2012. He has authored and co-authored more than 150 international publications and holds three patents.
Dr Tang Tong Boon current position as Director of Institute of Health and Analytics and Associate Professor of Electrical and Electronic Engineering Department, Universiti Teknologi PETRONAS. Tang Tong Boon received his received the B.Eng. degree (Hons) and Ph.D. degree from The University of Edinburgh. His research interests are in biomedical image analysis and artificial intelligence. He received the Lab on Chip Award in 2006 and the IET Nanobiotechnology Premium Award in 2008. He serves as the Secretary of the Higher Centre of Excellence (HICoE) Council and the Chair of the IEEE Circuits and Systems Society Malaysia Chapter.
5. Dr Eric Ho Tatt Wei
Dr Eric current position as Senior Lecturer at Electrical and Engineering Department, Universiti Teknologi PETRONAS. Experts on deep neural network technology to network analysis on MRI brain images. Eric Ho Tatt Wei received his MS and PhD degrees in Electrical Engineering from Stanford University in Silicon Valley, USA specializing in computer hardware and VLSI systems, As part of his PhD research, he developed real-time systems for fruit flies for biological research to conduct automated inspection and guide robotic manipulation. He is currently pursuing applications of deep neural network technology to network analysis on MRI brain images.
*fee quoted does not include SST, GST/VAT or withholding tax (if applicable)
*fee quoted does not include SST, GST/VAT or withholding tax (if applicable)
Centre for Advanced & Professional Education (CAPE)
Level 16, Menara 2,
Menara Kembar Bank Rakyat,
50470, Jalan Travers,
Kuala Lumpur.
+605 - 368 7558 /
+605 - 368 8485
cape@utp.edu.my