Machine learning (ML) is the use and development of computer systems with the ability to learn and discover patterns in data. You even encounter some of these systems on a daily basis; for example, a computer program can determine whether an email is spam or not spam, and a computer program can find patterns among shoppers and recommend products tailored toward their needs and interests. Learning to analyze and visualize data in meaningful ways is a critical step in your study of ML.

In this course, you will start by exploring the role that machine learning plays in the industry for decision making and its impact on your role. The characteristics of a particular problem, the data you have to work with, and the questions you want to answer will dictate what type of ML approach, method, and algorithm needs to be used. Once you cover the basic role of machine learning and the process from start to finish, you will gain experience in industryrelevant tools such as Jupyter Notebooks, NumPy, and Pandas.