PRG/211T
Algorithms and Logic for Computer Programming

Course level: Undergraduate

Christine O.

BSA

Need help enrolling in a single course? Call 866-354-1800 or schedule a call.
Format
Online
Course length
5 weeks
Cost per credit
$426
Total credits
3 credits
Resource fees
$180
Estimated course cost
$1,458
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Start date
Nov 17, 2026 to Dec 21, 2026
Enroll by 6 PM Phoenix: Nov 12, 2026
46872164
Start date
Jan 05, 2027 to Feb 08, 2027
Enroll by 6 PM Phoenix: Dec 31, 2026
46881920
Start date
Feb 09, 2027 to Mar 15, 2027
Enroll by 6 PM Phoenix: Feb 04, 2027
46890675
Start date
Mar 16, 2027 to Apr 19, 2027
Enroll by 6 PM Phoenix: Mar 11, 2027
50947226
Start date
Apr 20, 2027 to May 24, 2027
Enroll by 6 PM Phoenix: Apr 15, 2027
50947242
Note
Take this course on its own, or as part of a degree or certificate program.
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Format details

Online classes, always on, 24/7/365

Go to class any time of the day or night. If you have questions, call 866-354-1800 to speak with an Enrollment Representative.

This course provides students with a basic understanding of foundational programming concepts and development practices. Concepts covered include the application of algorithms, logic, and computational thinking to the design and analysis of solutions for business information systems. Students learn to model and evaluate program logic using tools such as flowcharts and pseudocode before implementing procedural and object-oriented programming concepts, including data types, control structures, functional decomposition, arrays, classes, and objects.

Required materials

The materials required for this course are covered in your resource fees.

Earn these career-relevant skills in weeks, not years.

Algorithms

Examine modular solutions using functional decomposition and introductory object-oriented concepts to organize and explain program behavior

Troubleshooting

Evaluate systematic debugging and troubleshooting strategies to trace algorithmic behavior and diagnose common error patterns

Programming Concepts

Apply input, process, and output models to analyze algorithms and identify logic errors