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Nov 02, 2024
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CS 2300 - Computational Science3 lecture hours 2 lab hours 4 credits Course Description An introduction to the science of computation and data including tools, languages, and methods to support artificial intelligence. Topics include applying the scientific method for data-driven computational problems, analysis, data preparation, and visualization. (prereq: CS 1021 ) Course Learning Outcomes Upon successful completion of this course, the student will be able to:
- Learn and apply the scientific method to data analysis and inference
- Clean and manage data using functional programming libraries such as pandas
- Use matrices and software libraries to structure data for analysis and manipulation
- Manipulate models of real-world problems based on data
- Predict the runtime and memory utilization of algorithms based on complexity analysis methods
- Communicate data interpretations including generating meaningful data visualizations
Prerequisites by Topic Coordinator Dr. Derek Riley
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