Theories and Applications in Artificial Intelligence

This course will introduce the fundamental theories and applications of Artificial Intelligence (AI). AI is widely considered as one of the most important technologies in recent years. Its impacts have been significant in many fields including business, manufacturing, education, healthcare, transportation, etc. This course will cover the recent developments in AI and introduce some important AI models and architectures including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short Term Memory (LSTM), emerging trends such as Transformers and their relevant applications. At the end of the course, participants will have a good understanding of these important AI models, theories and their applications.

Dr. Kim-Hui YAP received the Bachelor of Engineering (University Medal Winner and First Class Honors) from the University of Sydney, Australia, and Ph.D. degree from the same university. He has been a faculty member with Nanyang Technological University (NTU), Singapore since 2002. His main research interests include artificial intelligence, computer vision, data / image / video processing, and pattern recognition.

Dr. Yap has served in a number of roles in NTU over the years including the Assistant Chair (Faculty) of the School of EEE, the Deputy Chairman of School Faculty Committee, the MSc (Signal Processing) Program Director, and the Committee Member in different Working Committees. He has also served in national and international organizations including Technical Committee Member on Multimedia Representation for ITSC, Technical Expert Panel Member for MDA IJAM Program, Associate Editor and Editorial Board Member for several international journals, Organizing Committee Member for different international conferences, and Committee Member in several IEEE Singapore Chapters.

This course aims at providing you with a good understanding of the fundamental theories and applications of AI. You will learn different models of AI including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short Term Memory (LSTM), emerging trends such as Transformers and their relevant applications.

If you are interested in the theories and applications of AI, you should take this course. This course will equip you with the key knowledge of AI for your future advancement in the relevant fields.

Session 1: Introduction to Artificial Intelligence (AI)

History of AI, Deep Neural Network (DNN) architectures, linear classifier, AI resources Session

Session 2: Convolutional Neural Networks (CNNs)

Theory of CNNs, CNN architecture, training of CNNs, well-known CNN models

Session 3: Recurrent Neural Networks (RNNs)

Theory of RNNs, RNN architecture, training of RNNs, theory of LSTMs, LSTM architecture

Session 4: Emerging Trends in AI & AI Applications

Emerging trends in AI such as Transformer, Generative Adversarial Network, etc. Recent AI applications including image classification, time-series prediction and forecasting, etc.

Session 5: Group Presentation by Participants

Teamwork and group presentation by participants

Theories and Applications in Artificial Intelligence

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