WHEN
27-29 July 2021
WHERE
MS TEAMS (ONLINE)
TIME
9.00 AM - 5.00PM
RM 2,450 FOR PROFESSIONALS
10% Discount for Early Bird (26 June 2021) / Group / Students
COURSE SUMMARY
INTRODUCTION
This course is designed to expose the participants with the concept of machine learning models for predictive analytics (theory + case study). This course includes hand on approach using real world datasets, to test different models and visualize the outputs with different machine learning models which can later be directly applied by the participants to the job.
Module 2:
Module 3:
OBJECTIVES
Upon completion of this course, participants will be able to:
Understand the implementation of Big Data Analytics that can help in improving management decision-support effectiveness.
WHO SHOULD ATTEND?
1. Dr. Mohd Hilmi Hasan (UTP)
Dr. Izzatdin is an Associate Professor and Deputy Head at the Centre for Research in Data Science (CeRDaS) in Universiti Teknologi PETRONAS (UTP), where he focuses on solving complex upstream Oil and Gas (O&G) industry problems from the view point of computer science. He obtained his Ph.D in Information Technology from Deakin University, Australia working in the domain of hydrocarbon exploration. Prior to his Ph.D, Izzatdin earned his Master’s degree in Information Technology specializing in Computer Networks from the University Of Sydney, Australia. Izzatdin has secured and delivered numerous computing-related O&G projects mainly relating to seismic data processing and implementation of workflows for processing hydrocarbon exploration dataset on cloud-based systems. He is working closely with O&G companies in delivering solutions for complex problems such as Offshore O&G pipeline corrosion rate prediction, O&G pipeline corrosion detection, securing data on clouds and designing and implementing Metocean prediction system. Additionally, he is also working on Big Data transmission, security and optimization problems on High Performance Computing Clusters. His research is mainly funded by the Petroleum Research Fund, PETRONAS and The Malaysian Ministry of Higher Education.
3. Dr. Said Jadid (UTP)
Dr. Said Jadid, is currently a Lecturer at the Department of Computer and Information Sciences, Universiti Teknologi PETRONAS (UTP). He holds a Degree in Computer Science from Moi University (2009), Master’s Degree in Computer Science from Universiti Teknologi Malaysia (2012) and a PhD in Information Technology from Universiti Teknologi PETRONAS (2016). His research interests are in the areas of Machine Learning (Supervised Learning) and Data Analytics (Predictive and Streaming Analytics). He has been appointed as a reviewer for Artificial Intelligence Review (Q2 Journal) and a technical committee for various international conferences.
Dr. Hitham Alhussian received his BSc and MSc in Computer Science from the School of Mathematical Sciences, University of Khartoum (UofK), Sudan. He obtained his PhD from Universiti Teknologi PETRONAS (UTP), Malaysia. Following his PhD, he worked as a Post Doctorate Researcher in the High-Performance Cloud Computing Center (HPC3) in UTP. He is currently, a Senior Lecturer in the department of Computer and Information Sciences in UTP and a core member of Centre for Research in Data Science (CERDAS). His main research interests include real-time parallel computing, big data and cloud computing, machine learning and data mining.
*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