BAN 315 - Data Analysis with Python II

Units: 3
This course further develops students’ capability of performing quantitative and computational data analysis with Python libraries such as Pandas, NumPy, SciPy, Scikit-Learn, TensorFlow, and PyTorch.

Prerequisites: BAN 310
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 linear algebra and matrix calculus.
apply those concepts in building data models.
use appropriate software in implementing the matrix-based data models to solve business problems, interpret results and write recommendations.