Intelligent Transformation of Businesses
Dates: 11 Mar, 12 Mar 2024 | 9am-5.30pm | Online
Duration: 2 Days
Course Overview
Artificial Intelligence (AI) and Machine Learning (ML) have significantly changed businesses and business ecosystems across almost all sectors. Especially, as disruptive technologies, AI and ML are developing new applications and increasing business performances. AI and ML can automate different business processes and use data to devise predictive systems and high-performance decision supporters. Meanwhile, hardware robots and software chatbots are going to replace human operators in many activities. This way, we can give the workforce more time for business development, troubleshooting, and creativity. Typically, the homogeneity and speed of AI/ML-driven systems would be higher. The important question to ask is how we can make our business AI/ML-ready and transform it into an intelligent business. During this course, we are going to help participants to find proper answers to those important questions.
This course is part of Professional Certificate in Artificial Intelligence and Machine Learning Foundation for Executives.
Course Objectives
This course presents a solid definition of digitalization, digital transformation, and intelligent transformation of businesses. It helps participants to understand AI and ML capabilities of their business. Articulating different approaches and methodologies of intelligent transformation of businesses. The participants will be practicing intelligent transformation based on some real-world scenarios.
Who Should Attend
AI/ML Executives, Digital Transformation PM
Prerequisites
Basic IT and Math knowledge
Course Convener
(Click their photos to view their short biographies)
Dr Amirhassan Monajemi
Dr Amirhassan Monajemi
Dr Amirhassan Monajemi is a Senior Lecturer in AI and Machine Learning with the School of Computing (SoC) at the National University of Singapore (NUS). Prior to SoC, he was a Senior Lecturer in NUS School of Continuing and Lifelong Education (SCALE) teaching AI and Data Science to adult learners. Before joining NUS, he was with the Faculty of Computer Engineering, University of Isfahan, Iran, where he was serving as a professor of AI, Machine Learning, and Data Science. He was born in Isfahan, Iran. He studied towards BSc and MSc in Computer Engineering at Isfahan University of Technology (IUT), and Shiraz University respectively. He got his PhD in computer engineering, pattern recognition and image processing, from the University of Bristol, Bristol, England, in 2005. His research interests include AI, Machine Learning, Machine Vision, IoT, Data Science, and their applications.
He has taught the artificial intelligence courses, including AI, Advanced AI, Expert Systems, Decision Support Systems, Neural Networks, and Cognitive Science since 2005 at both undergraduate and postgraduate levels. He was awarded the best university teacher of the province in 2012. He also has studied Learning Management Systems, E-Learning, and E-Learning for workplaces since 2007.
Dr Monajemi has registered a few patents in the fields of AI, Machine Vision, and Signal Processing applications, including an AI and machine vision-based driver drowsiness detection system and a low power consuming spherical robot. He also has published more than a hundred research papers in peer-reviewed, indexed journals and international conferences (IEEE, Elsevier, Springer, and so on), and supervised several Data Science, IoT, and AI industrial projects in various scales, including Isfahan intelligent traffic system delivery and testing, and red light runners detection. He is experienced in different sub-domains of Artificial Intelligence and Machine Learning, from theory to practice, including Deep Learning, Logic, and Optimisation.
Course Fees
Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes
GST shall apply at prevailing rates
Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
To enquire, email soc-ace@nus.edu.sg
To register, click Register
Course Codes
TGS-2022012310 (Classroom Learning)
TGS-2022012295 (Synchronous e-learning)
Course Fee Breakdown
Singapore Citizens
39 years old or youngerSingapore Citizen
40 years old or older
