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Aug 31, 2024
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SDEV 121 - Python for Data Analytics Credits: 5 Problem solving and algorithm development are emphasized as students learn Python, the most widely-used data science programming language. Students learn how to write Python programs to process data sets and gather insights from interpreting data.
Enrollment Requirement: CS 108, CS 109 or CS 120 /ENGR 120 with a grade of 2.0 or higher; or instructor consent.
Course Outcomes: Students who successfully complete this class will be able to:
- Write a program that reads and processes data from a file.
- Recognize common data file formats (e.g. comma-separated values, JSON).
- Apply Python data structures (e.g. lists and dictionaries) to store and organize data in memory for processing.
- Apply Python control structures (e.g. decision and iteration) to support data analysis techniques such as filtering and calculating aggregate values.
- Apply Python variables and expressions to support calculation of values.
- Apply (call) library functions from the standard Python library (e.g. strings, random) to support data processing.
- Apply (call) library functions from third-party libraries (e.g. NumPy, pandas) to support data processing.
- Write a Python program that is decomposed and organized into multiple functions.
Program Outcomes
- Solve data-related problems using a programming language.
- Demonstrate the ability to acquire, clean, and prepare data for analysis.
- Perform basic data analysis techniques such as filtering, aggregation, and joins.
College-wide Outcomes
- Quantitative and Symbolic Reasoning - Quantitative Reasoning encompasses abilities necessary for a student to become literate in today’s technological world. Quantitative reasoning begins with basic skills and extends to problem solving.
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