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Fall 2022
Jun 27, 2022
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Information Select the desired Level or Schedule Type to find available classes for the course.

ME 53900 - Introduction To Scientific Machine Learning
Credit Hours: 3.00. Introduction to the fundamentals of predictive modeling for advanced undergraduates and graduate science and engineering students that work in the intersection of data and theory.
3.000 Credit hours

Syllabus Available
Levels: Graduate, Professional, Undergraduate
Schedule Types: Distance Learning, Lecture

Offered By: School of Mechanical Engr
Department: Mechanical Engineering

Course Attributes:
Upper Division

May be offered at any of the following campuses:     
      West Lafayette Continuing Ed
      West Lafayette

Learning Outcomes: 1. Represent mathematically the uncertainty in the parameters of physical models. 2. Propagate parametric uncertainty through physical models to quantify the induced uncertainty in quantities of interest. 3. Calibrate the uncertain parameters of physical models using experimental data. 4. Combine multiple sources of information to enhance the predictive capabilities of models. 5. Pose and solve design optimization problems under uncertainty involving expensive simulations or experiments. 6. Improve scientific writing and data visualization skills.


Restrictions:
May not be enrolled as the following Classifications:     
      Sophomore: 45 - 59 hours
      Sophomore: 30 - 44 hours
      Freshman: 0 - 14 hours
      Freshman: 15 - 29 hours

Prerequisites:
GR ME 53900 Requisites

General Requirements:
Course or Test: MA 41600
Minimum Grade of D-
May not be taken concurrently.
and
Course or Test: ME 58100
Minimum Grade of D-
May not be taken concurrently.  )
or

Student Attribute: GR
May not be taken concurrently. )


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