Solving Problems with Machine Learning

Dwight Nuwan Fonseka is Head of Data Science at Plano Pte. Ltd. and an ACLP-certified trainer with deep expertise in data analytics, machine learning, and AI applications. He has extensive hands-on experience developing predictive models, RShiny dashboards, and deep learning solutions using R, Python, TensorFlow, and Keras. With a strong professional background in healthcare, finance, and customer analytics, Dwight brings an applied perspective to teaching AI, focusing on both the opportunities and risks of emerging technologies.

Richard Wan is an ACLP-certified lecturer and software consultant with over 40 years of experience in software and hardware development, spanning AI, computer vision, and machine learning. He began his programming career with 8-bit computing in the late 1970s and went on to earn his M.Sc. in Electrical Engineering (Computer Vision) from the University of Wisconsin–Madison. His professional contributions include co-founding multiple high-tech companies, pioneering digital publishing technologies, and leading AI-driven software development in healthcare, defense, and manufacturing.

Richard has taught a wide range of technical courses, including machine learning with Scikit-Learn, deep learning with TensorFlow and PyTorch, and computer vision with OpenCV. In predictive analytics, he emphasizes the use of PyTorch for building deep learning models that can forecast trends, detect anomalies, and classify outcomes. His teaching approach blends decades of hands-on development with structured, beginner-friendly instruction, equipping learners with practical skills to transform data into prediction.