BAN 310 - Data Analysis with Python I

Units: 3
This course introduces widely-used Python libraries for exploratory and quantitative data analysis, including NumPy, Pandas, Statsmodels, and Matplotlib, along with conceptual foundations such as statistical inference, regression, and matrix for better understanding and mastery of the data analysis toolkits.

Prerequisites: MATH 130 and CS 100 (or CS 101)
Possible Instructional Methods: On-ground, or Hybrid, or Online Asynchronous or Online Synchronous.
Grading: A-F grading only.
Course Typically Offered: Fall & Spring

Student Learning Outcomes - Upon successful completion of this course students will be able to:

identify appropriate quantitative tools and methods to solve business problems;
identify appropriate technology tools to solve business problems;
use data analytics models in making effective business decisions;
employ technology to analyze data and to aid decision-making;
explain analytical results in their project reports and other assignments to people with technical and non-technical backgrounds.
demonstrate understanding of the fundamental concepts of probability and statistics
apply those concepts in drawing statistical inference, and building models.
use appropriate software in implementing the statistical models to solve business problems, interpret results and write recommendations.