2025 ASEE Annual Conference & Exposition

Abstract

Artificial Intelligence (AI) is the branch of computer science dedicated to creating systems or machines that can perform tasks that typically require human intelligence. These tasks include problem-solving, reasoning, understanding natural language, recognizing patterns, learning from experience, and making decisions. AI systems aim to mimic or simulate cognitive functions such as thinking, learning, and decision-making. AI is the science of building machines or software that can think, learn, and act in ways that seem intelligent, often simulating human-like behavior.

Machine learning (ML) is the study of computer algorithms that can improve automatically through experience and by the use of data. Machine learning is a subset of Artificial Intelligence. Machine learning algorithms build a 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 algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, and computer vision, where it is difficult to develop conventional algorithms to perform the tasks needed [1-3].

ML is an emerging area of importance for a wide range of applications. ML has become a revolutionary modern engineering tool to solve real-world engineering problems. 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. Because of the availability of computing power, more and more engineering problems have been reformulated and solved using this data-driven approach.

The field of machine learning is growing rapidly. It is essential that the emerging field of machine learning be integrated into the electrical and computer 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 in their electrical and computer engineering curricula.
.