CIV 355 - Data Analytics for Civil Engineering Systems
Current Catalog Description
An introduction to the fundamentals of descriptive and predictive analytics. Basic methods, models, and tools of data analytics for analyzing, understanding, and managing civil engineering systems in a data-driven approach
Prerequisite
CIV 305
Corequisite:
None
Textbooks and/or Other Required Material
No textbook is required. Microsoft Excel, R.
This course is
Not Required
Topics Covered
- An introduction to data analytics in civil engineering
- Data description
- Data visualization
- Modeling uncertainty using probability
- Statistical inferences
- Monte Carlo simulation
- Regression analysis
- Time series analysis
- Clustering
- Classification
Course Learning and Student Outcomes
Understand any given problem of study in the civil engineering context and from the perspective of data analytics. ABET Student Outcome: 1
Identify appropriate methods of data analysis, formulate the solution approach, collect new data or select existing data, and prepare the data for analysis; ABET Student Outcome: 1
Perform data exploration,data description, data visualization, and data mining to develop an understanding of data; ABET Student Outcomes: 6
Train, validate, and test predictive models to build the ability to predict or estimate the system measurements of interest; ABET Student Outcome: 6
Summarize and interpret analysis results to develop the final recommendation for system improvement. ABET Student Outcomes: 3, 6
Prepared by
Ruwen Qin (2021)
Last Updated:
4/2021