Haptics in Aviation

Abstract According to Wikipedia "machine learning is the study of computer algorithms that improve automatically through experience. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to do so". Machine learning has many applications such as banking, bioinformatics, adaptive websites, computer networks, economics, linguistics, online advertising, self-driving cars, dynamic pricing, traffic alerts, social media, search engines, speech recognition, online video streaming, IOT, … Machine learning has become a revolutionary modern engineering tool to solve real-world engineering problems. Because of availability of computing power, more and more engineering problems have been reformulated and solved using this data-driven approach. It is essential for engineers to know how to apply machine learning algorithms to their large amount of data that is generated by the sensors. Educational excellence requires exposing students to the current edge of research. To ensure that student projects are along the same trajectory that the industry is moving, educators must continually introduce emerging techniques, practices, and applications into the curriculum. The field of machine learning is growing rapidly. It is essential that the emerging field of machine learning be integrated into the computer science and engineering curricula. This paper is a study of different approaches that are used by different institutions of higher education around the world to integrate machine learning concepts in their computer science and engineering curricula.