BAN218

INTRO TO PYTHON PROGRAMMING

This course is offered in a current or upcoming term. Check the official course schedule before registering.
Terms offered
1
Data refreshed
Jun 27, 2026

Description

Analytics Programming, designed as a practical introduction to data analytics in a business context. Aimed at students with minimal programming experience, this course focuses on Python programming and its Pandas library as primary tools for data manipulation and analysis. The course is not merely a technical tutorial but an application-oriented guide. You'll learn how to define business problems clearly, ask insightful questions, and then use Python and Pandas to uncover answers. We will start with Python fundamentals and move on to more complex data manipulation and visualization techniques using Pandas. Throughout the course, you'll engage in hands-on mini-projects that simulate real-world business scenarios, culminating in a team-based final project. This final project serves as both a capstone experience and a portfolio piece, demonstrating your newfound analytical skills in a real-world context. By the end of this course, you'll have both the technical skills and the strategic mindset to apply data analytics effectively in any business environment.

Syllabi

Sign in with your @clarku.edu email to view syllabi.

Offering history & forecast 2026

2026

Sections offered by academic year and season, with estimated offering chances for future years above the divider
YearFallSpringSummerIntersession
2030 2030 Fall: not enough history to forecast. 2030 Spring: not enough history to forecast. 2030 Summer: not enough history to forecast. 2030 Intersession: not enough history to forecast.
2029 2029 Fall: not enough history to forecast. 2029 Spring: not enough history to forecast. 2029 Summer: not enough history to forecast. 2029 Intersession: not enough history to forecast.
2028 2028 Fall: not enough history to forecast. 2028 Spring: not enough history to forecast. 2028 Summer: not enough history to forecast. 2028 Intersession: not enough history to forecast.
2027 2027 Fall: not enough history to forecast. 2027 Spring: not enough history to forecast. 2027 Summer: not enough history to forecast. 2027 Intersession: not enough history to forecast.
2026 1 section Not offered Not offered No data for this term
Forecast Under 15% 15–39% 40–69% 70–89% 90%+ Not enough history
Fall Spring Summer Intersession Darker means more sections Not offered No data for term

Future estimates combine recent offering frequency with detected multi-year cycles. Hover a cell for confidence and evidence; low-confidence estimates are marked with ~.

Meeting times

Most recent first
  • Tue, 6:00 PM–9:00 PM JC218 2026
Credit-bearing sections of BAN218
TermProfessorTypeCreditsEnrollmentCRN
Fall 2026Kyunghee YoonLecture1 1 of 5 enrolled24883