AI APPLICATION IN EXPERIMENTAL DATA ANALYSIS TIME-SAVING SOLUTION FOR ENGINEERING STUDENTS

Abstract

During their studies and practice, engineering students often encounter difficulties in collecting,
processing, and analyzing experimental data due to its complexity and large volume. This paper proposes
the application of artificial intelligence (AI) as an effective solution to support the analysis and visualization
of experimental data. By utilizing popular AI tools such as Python, machine learning libraries, and
analytical models, students can reduce the time required for report writing, minimize errors, and enhance
critical thinking. The paper presents several examples of AI applications in electrical, mechanical, and
automation experiments, emphasizing the practical benefits in developing digital skills and improving
learning outcomes. It also recommends integrating AI into training programs and encourages students
to adopt this technology as an indispensable learning and research tool in the digital transformation era.