Date: 20 Oct 2023 | 9am – 5.30pm | Online
Duration: 1 Day
Course Overview
Octave is an open-source interactive programming language widely used in machine learning and data analytics courses. Designed primarily for matrix computation, Octave is a powerful tool that enables the development of efficient engineering, data analytics and machine learning programmes.
Its simple syntax and supportive environment lets learners to focus on the concept and relations. Through the effective application of Octave programming, learners would be able to solve a diverse set of data analytics and machine learning problems. It gives learners a deeper knowledge of how and what in those areas as well.
This course is part of Professional Certificate in Artificial Intelligence and Machine Learning Basics.
Course Objectives
At the end of the course, participants will be able to:
• Use the Octave environment.
• Develop codes in Octave.
• Install and use Octave toolboxes.
• Apply Octave in data analytics and machine learning.
Who Should Attend
IT engineers, IT executives, Fintech executives and system developers.
Prerequisites
Basic mathematics and basic IT knowledge
Course Convener
(Click photo to view biography)
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
Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
NTUC members enjoy 50% unfunded course fee support for up to S$250 each year (or up to S$500 for NTUC members aged 40 years old and above) when you sign up for courses supported under UTAP (Union Training Assistance Programme). Please visit e2i’s website to find out more.
To enquire, email soc-ace@nus.edu.sg
To register, click Register
Course Codes
TGS-2020513881 (Classroom Learning)
TGS-2020504956 (Synchronous e-learning)
Course Fee Breakdown
Singapore Citizens
39 years old or youngerSingapore Citizen
40 years old or olderYou may also like to view:
Catalogue of Programmes for Individuals
- Course Category
- Artificial Intelligence & Machine Learning
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