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Applied Machine Learning with Generative AI

Programme Overview

This course introduces participants to Applied Machine Learning and Generative AI methods and their impacts on AI, emphasizing hands-on implementation and real-world applications. Participants will learn how to build and deploy models with a focus on generative models used for content generation, data augmentation, and other creative or problem-solving tasks. By the end of the course, participants will be proficient in building and applying Generative AI Models across multiple domains such as images and video.

Learning Objectives

At the end of the course, participants will be able to:

  • Establish a solid foundation in generative models and understand their diverse applications in AI.
  • Delve into Generative Adversarial Networks (GANs), their architectures, training challenges, and applications.
  • Understand transformers and Large Language Models (LLMs).
  • Explore generative models in image and video domains and the tools used to implement them.

Instructors


Dr Amirhassan MonajeminDr Amirhassan Monajemi

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.
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NUS Computing, Advanced Computing for Executives (ACE)

11 Research Link
COM 3, #B1-07
Singapore 119391

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