|Use this page to maintain syllabus information, learning objectives, required materials, and technical requirements for the course.|
|CS 50023 - Data Engineering I|
Learning Outcomes: 1. Identify key file types (TXT, CSV, HTML) and their characteristics. Using Python, read data in these formats. 2. Create and execute Python scripts to parse, select, transform, summarize, and visualize data. 3. Explain how to identify and fill in missing values in data values. 4. Create informative visualizations from given data and recognize the key qualities of good visualizations. 5. Apply Pandas functions to slice, dice, and summarize datasets. 6. Apply the process of sampling data and sample probabilistically. 7. Demonstrate how to transform and construct features (e.g., standardization, distances). 8. Compute summary statistics from data (e.g., covariance, correlation). 9. Explain how to solve simple data analysis problems.
|Return to Previous||New Search|