Overview This course is designed for individuals who wants to understand what AI is and its applications at work. Part 1 – The intuition of AIIn this workshop, we explore the derivative of what empower some of the most common AI solutions. Participants will have a hands-on basic artificial neural …
Overview This course consists of 3 full-day sessions covering hands-on session using both commercial software and open source networks for developing deep learning models. This would enhance the understanding of deep learning principles. At the end of the course, the participants will be able to develop deep learning models for …
Overview This course aims to introduce concepts in Design and Generative AI. Techniques to adopt Generative AI in the Design process will be covered. Learners will acquire skills in coding a workflow for Generative AI applications based on a Design framework. The course is targeted for learners in design and …
Overview The aim of this module is to provide a business deployment perspective of foundational Deep Learning AI capabilities, ranging from Natural Language Processing to Machine Vision; in a manner that requires little or no coding. Neural networks and how Deep Learning works, the data input requirements, project lifecycle, and …
Overview This course will equip participants with the technical skills to apply machine learning algorithms and deploying practical Artificial Intelligence (AI) models with an industrial edge controller for anomaly detection and predictive maintenance. The course will also cover the essential concepts and background for data analysis on supervised and unsupervised …
Overview There has been renewed interest learning in artificial intelligence (AI) and machine learning in recent years. This is fuelled by the recognition that data generated contains a wealth of information that could be distilled from it. This course helps to provide and introduction to the fundamentals of AI and …
Overview This applied learning workshop comprises two learning phases: Phase 1 (2 days) prepares participants with the foundational skills and knowledge required to get started with machine learning development. In this phase, we explain the various machine learning techniques, share use cases, prepare machine learning-ready data, perform modelling and prediction, …
Overview This course aims to provide participants with knowledge, techniques and skills in data collection, analysis for predictive maintenance and optimal maintenance planning. Data from machine sensors, operation management systems and maintenance activities are analyzed during the training sessions. The latest technology, for example, machine learning based predictive engines and …
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