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.

Prerequisite: CS 108 or CS 109 with a grade of 2.0 or higher; or instructor’s permission.

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.