An introductory graduate level course in Machine Learning (ML), primarily focused on mechanical engineering applications. The primary goal of this course is to equip students with theoretical and practical knowledge of ML and its advancements in mechanical engineering. The course will introduce supervised and unsupervised learning, data modeling, data reduction methods, neural networks, reinforcement learning, and deep learning. The course will use MATLAB as its main programming language for developing ML models. The students will also be introduced to the state-of-the-art ML models utilized in mechanical engineering disciplines including but not limited to robotics, dynamics, design, heat transfer, fluid mechanics, and manufacturing, through a review of high-impact journal articles. Students will develop ML models for real-world mechanical engineering applications as part of their course project.