Dr. Wenyuan Tang
Electrical and Computer Engineering
ECE 592 613 Data Analytics for Power Engineering
3 Credit Hours
Introduction to data science and Python programming. Exploratory data analysis in power systems. Classical machine learning methods. Deep learning with PyTorch. Power system optimization with Gurobi. Big data applications in power systems.
Engineering graduate student. A background in power systems is helpful but is not required.
- Understand the data science workflow.
- Learn the Python programming language for data science.
- Conduct exploratory data analysis.
- Apply supervised and unsupervised machine learning methods.
- Implement deep neural networks with PyTorch.
- Use Gurobi to solve optimization problems in power systems.
- Apply data analytics tools to solve a practical problem in power and energy systems.
Computer and Software Requirements
Please review minimum computer specifications recommended by NC State University and Engineering Online.