The College of Engineering be offering a new senior elective/graduate-level course in the 2021 spring semester, which should be of interest to students who are interested in learning about new data-driven methods to build and analyze models of complex engineering systems such as mechanical systems, processes, phenomena.
MECH 492/892: Data-Driven Science and Engineering
Spring 2021, MWF 2:30-3:20
Instructors: Dr. Prahalada Rao, Dr. Eric Markvicka, Dr. Piyush Grover, and Dr. Keegan Moore
Prerequisites: MECH 321, Math 314, and CSE 155N or equivalent
About the course: This course will introduce data-driven methods with a special focus on engineering applications. Data-driven methods are revolutionizing how we model, predict, and control complex systems such as robotics, manufacturing, and turbulent fluid flow. This course will cover the mathematical background required and introduce the data-driven approaches listed below. Evaluation will consist of problem sets and programming projects in MATLAB targeting real-world engineering applications.
Topics Covered:
• Basic statistics
• Supervised and unsupervised machine learning
• Neural networks
• Deep learning
• Fourier and wavelet transforms
• Data-driven time series analysis
Please direct all questions to Cherie Crist: ccrist8@unl.edu