TEACHING DESIGN OF DATA SCIENCE MODULES FOR MECHANICS GRADUATE STUDENTS IN THE BIG DATA AND ARTIFICIAL INTELLIGENCE ERA

Big data and artificial intelligence are flourishing and rapidly penetrating into fundamental research and engineering technologies. In advanced applied mathematics and related courses for mechanics graduate students, developing data science modules at an intermediate level between foundational courses and specialized academic reports can effectively narrow the gap between teaching and scientific research. This approach significantly enhances graduate students' capabilities in solving complex scientific problems. This paper introduces the instructional design of data science topics, along with teaching reflections and typical case studies from educational practice.