FUNDAMENTALS OF INDUSTRIAL DATA ANALYTICS
Provides an understanding of the fundamentals of using data analytics to make data-driven decisions. Emphasizes applying techniques to industrial engineering problems. Focuses on formulating and solving real industrial problems with the appropriate modeling strategies and analytics principles for better decision making.
Prerequisites & course information
Requisites: ( I SY E 210 , B M E 325 , E C E 331 , STAT 311 , 324 , MATH/STAT 309 , 409, 431 , MATH 331 , or 531 ), graduate/professional standing, or member of Engineering Guest Students Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Apply fundamental knowledge of industrial data analytics concepts, problems, and techniques Audience: Undergraduate 2. Integrate data analytics techniques with industrial and systems engineering domain knowledge to appropriately formulate problem statements and facilitate decision making Audience: Undergraduate 3. Implement software programming skills to perform data analysis Audience: Undergraduate 4. Apply industrial data analytics methods and tools to solve real-world industrial engineering problems Audience: Undergraduate Learning Outcomes: 1. Apply fundamental knowledge of industrial data analytics concepts, problems, and techniques Audience: Undergraduate 2. Integrate data analytics techniques with industrial and systems engineering domain knowledge to appropriately formulate problem statements and facilitate decision making Audience: Undergraduate 3. Implement software programming skills to perform data analysis Audience: Undergraduate 4. Apply industrial data analytics methods and tools to solve real-world industrial engineering problems Audience: Undergraduate
Sources
- Course catalogue ↗2026-2027