AIN 380 - Introduction to Applied Machine Learning

4 Hour(s)
This course introduces students to the fundamental machine learning methods that have proven successful in practical applications. This course focuses more on the practical and applied aspects of machine learning rather than on theory. Machine learning is an application of artificial intelligence (AI) that focuses on computer systems that can adapt and improve automatically over time with increased data experience. It has been essential to the success of many recent technologies including search engines, automated medical diagnostics, autopilot commercial flight systems, image recognition, social network analysis, genomics, biochemical interactions analysis, navigation systems such as Google Maps, financial applications such as credit card fraud detection, investment portfolio analysis and future stock price predictions, autonomous vehicles, recommendation systems used by Netflix and Amazon and others, advertising, and data analysis in IoT applications. This course introduces the basic concepts and algorithms that enable computers to learn from experience, with a strong emphasis on their practical application to real problems rather than in the statistical foundations and theory of Machine Learning. Students will make extensive use of high-level toolkits and APIs. In addition, this course will examine the ethical issues associated with machine learning applications.

FA-even years
Prerequisite(s): AIN 180 or AIN 210