Welcome to the Machine Learning and Deep Learning Open Lab Series! During this series, Dr. Namig Abbasov offers seven open labs to introduce participants to core concepts and techniques in Machine Learning (ML) and Deep Learning. These open labs will prioritize intuitive understanding of machine learning algorithms and deep learning approaches. These are intended to complement machine learning and deep learning courses taught at ASU by focusing on intuitive explanations of difficult concepts and examples with analogical illustrations. Below, you will find descriptions for each open lab of the series. Each open lab session is one hour long, allowing us to explore these topics as thoroughly as time permits.

The first open lab of the Machine Learning and Deep Learning Series, called Introduction to Machine Learning sets the stage for understanding machine learning by providing a foundational overview of its core concepts and applications. Participants will explore the different types of machine learning—supervised, unsupervised, and reinforcement learning—and their use cases. This session is designed for those new to the field, with no coding experience required. It will also highlight how machine learning drives modern technological advancements and introduce the field of deep learning. In addition, participants will gain insight into career opportunities in ML and strategies to start their learning journey. This session aims to leave participants with a strong conceptual understanding of machine learning’s potential.