CS 370 - Programming and Data Analysis for Managers

Credits: 5
Variable Credit Course: No

Lecture Hours: 55
Lab Hours: 0
Worksite/Clinical Hours: 0
Other Hours (LIA/Internships): 0

Course Description: Explore critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data and geographic data, document collections, and social networks. Investigate the workplace implications of ethical and social issues surrounding data analysis including bias and privacy.

Prerequisite: BASM Dept. Chair permission.
Meets FQE Requirement: No
Integrative Experience Requirement: No

Student Learning Outcomes

Recognize the benefits and limits of computing technology for data analysis and problem solving by examining its application in their field of professional interest.
Implement sequence, selection, and iteration by design an algorithm that solve a workplace problem in their field of professional interest.
Make accurate predictions by using statistical methods (confidence intervals, regression, hypothesis testing) and a programing language such as Python, to address workplace problems.
Demonstrate accurate representation of data such as histograms, bar charts, and box plots by using contemporary data visualization tools such as a Python library or Tableau.

Course Contents

Benefits and limits of computing technology for data analysis and problem solving.
Sequence, selection, and iteration by design an algorithm that solve a workplace problem in their field of professional interest.
Accurate predictions by using statistical methods (confidence intervals, regression, hypothesis testing) and a programing language such as Python, to address workplace problems.
Accurate representation of data such as histograms, bar charts, and box plots by using contemporary data visualization tools such as a Python library or Tableau.

Instructional Units: 5