This course offers an overview of some of the most widely used machine learning (ML) methods that are required for solving data science problems. We present the necessary fundamental for each topic and provide programming exercises. The course includes:

• The common practices for data pre-processing.
• Teaching different tasks regarding regression, classification, and dimensionality reduction using methods including but not limited to linear regression and classification, Support vector machines and Deep neural networks.
• Introduction to Python programming for data science.
• Applying machine learning models on real world engineering applications