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|CS 50023 - Data Engineering I|
Credit Hours: 1.00. The course introduces students to the fundamentals of Data Engineering with a focus on tools and computational techniques to gather, construct, manipulate, summarize, and visualize data sets as a means to extract knowledge from the underlying data. Python and Python libraries are used. Completion of the course will allow learners to perform basic data analysis on data sets. Experience in Python Programming and Linear Algebra is required. The course also prepares learners for additional instruction in the courses Data Engineering II and Foundations of Decision Making. Typically offered Fall Spring Summer.
1.000 Credit hours
Levels: Graduate, Professional, Undergraduate
Schedule Types: Distance Learning
Offered By: College of Science
Department: Computer Science
May be offered at any of the following campuses:
West Lafayette Continuing Ed
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.
Must be enrolled in one of the following Levels:
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