This course provides mechanical engineering students with practical knowledge in using machine learning (ML) and artificial intelligence (AI) to revolutionize materials design and manufacturing processes. Students will gain hands-on experience in building and managing databases, extracting meaningful data, and engineering features tailored to predict mechanical properties. Key skills include developing and optimizing machine learning models, conducting rigorous validation, and implementing active learning strategies to accelerate materials discovery. Through targeted case studies involving structural alloys, composites, and advanced ceramics, students will see firsthand how ML and AI enhance performance and innovation in mechanical engineering materials. Participants will utilize cutting-edge open-source tools such as scikit-learn and TensorFlow, alongside specialized platforms. By the end of the course, students will have built a practical portfolio showcasing their proficiency in applying informatics to mechanical engineering, preparing them for industry and research.