IMSE 433 - Industrial Data Analytics

(3 units)

Industrial Data Analytics is a course that covers the principles and practices of analyzing large data sets in industrial settings. Students learn about data acquisition, preprocessing, visualization, modeling, and interpretation from various sources. Emphasizes is on statistical analysis, machine learning, and data mining techniques used in industry. Students work with real-world data sets and be able to apply data analytics techniques to make data-driven decisions in industrial settings.

Maximum units a student may earn: 3

Prerequisite(s):STAT 352, CHE 245

Grading Basis: Graded
Units of Lecture: 3
Offered: Every Fall

Student Learning Outcomes
Upon completion of this course, students will be able to:
1. identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics.
2. recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts.
3. develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.

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