Go to Main Content

Purdue Self-Service

 

HELP | EXIT

Catalog Entries

 

Spring 2022
Jul 03, 2022
Transparent Image
Information Select the Course Number to get further detail on the course. Select the desired Schedule Type to find available classes for the course. The Schedule Type links will be available only when the schedule of classes is available for the selected term.

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.
1.000 Credit hours

Syllabus Available
Levels: Graduate, Professional, Undergraduate
Schedule Types: Distance Learning

Offered By: College of Science
Department: Computer Science

Course Attributes:
Upper Division

May be offered at any of the following campuses:     
      West Lafayette Continuing Ed
      West Lafayette

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 XML Extract
Transparent Image
Skip to top of page
Release: 8.7.2.4