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|CS 17600 - Data Engineering In Python|
Credit Hours: 3.00. The course introduces students to programming fundamentals in Python, including loops, functions and different data types, and provides an introduction to data engineering including working with common data formats and learning the basics of data wrangling. Students will format, extract, clean, filter, transform, search, combine, summarize, aggregate, and visualize a diverse range of data sets. Python libraries including MatPlotLib and Pandas are used.
0.000 OR 3.000 Credit hours
Levels: Undergraduate, Graduate, Professional
Schedule Types: Distance Learning, Laboratory, Lecture
All Sections for this Course
Offered By: College of Science
Department: Computer Science
May be offered at any of the following campuses:
Learning Outcomes: 1. Write Python code using loops, decision statements, and functions. 2. Explain how arguments are passed in Python functions and how the scope of variables impacts execution. 3. Use the operations on lists, tuples, and dictionaries to perform appropriate data manipulations. 4. Using Matplotlib, create informative plots and other data visualizations. Explain the key qualities of good visualizations. 5. Creating and manipulating DataFrames using Pandas. 6. Create Python code as well as methods in Pandas to select, search, change, and summarize data in tables. 7. Explain how to identify and fill in missing values in data. 8. Apply Pandas functions combine and merge datasets, perform a range of data aggregations, groupings and cross tabulations. 9. Given multiple data sets, demonstrate how to summarize, transform, combine the data sets, and aggregate and visualize the resulting data set.
Short Title: Data Engineering In Python