Most real-world AI applications involve applying machine learning to structured, tabular data. This course's objective is to provide students with practical, hands-on experience with state-of-the-art machine learning tools widely used in industry to solve science and engineering problems based on structured, tabular data. On completion of this course students will: 1. Implement complete machine learning pipelines using Scikit-Learn to solve supervised and unsupervised learning problems with a variety of techniques; 2. Understand various failure modes that can arise when training machine learning pipelines and be able to recognize and troubleshoot these failure modes in their own work; 3. Develop, train, deploy, and maintain complete machine learning applications. This course cannot be taken for credit for Computer Science students.