Lecture
This lecture provides an overview of the ME-301 course on measurement techniques, emphasizing both theoretical and practical aspects. It begins by highlighting the importance of data quality in data science and machine learning, stressing that understanding measurement techniques, their accuracy, and limitations is essential for modern engineers. The course aims to equip students with knowledge of experimental methodologies, sources of error, and basic signal processing tools. The theoretical part covers general measurement principles, specialized measurement systems, and signal processing. The practical component involves group projects where students design experiments to address mechanical engineering problems, select appropriate measurement devices, conduct measurements, and analyze data. Assessment methods include a final written exam and a technical report, with a focus on developing critical thinking and problem-solving skills. The lecture also outlines expectations for student engagement and collaboration, emphasizing the iterative nature of experiments and the importance of feedback in the learning process.