dynamicsystemsarchitecture.org

Programming for Systems Analysis

Stage I, Course 4 · 3 credits · 14 weeks · From theory to working software

Course CodePROG
StageI (Representation)
SequenceCourse 4 of 17
Credits3
PrerequisitesNone (basic programming helpful)
CorequisitesMathematics for Dynamic Systems (helpful)
StatusCore Required

Course Purpose

Students learn to implement systems thinking in code. This course answers: "How do we translate a system model into a computer program?" and "How does code clarify or obscure our understanding of systems?"

By end: Students can build simulations of dynamic systems, collect data from those simulations, analyze results, understand numerical methods and their limits, and use code as a tool for systems thinking.

Learning Outcomes

  1. Choose appropriate data structures to represent system state
  2. Implement differential and difference equations in code
  3. Build discrete-time simulations of systems
  4. Collect and visualize simulation data
  5. Test that code matches intent — debugging and verification
  6. Use simulation to explore system behavior — parameter sweeps, sensitivity analysis
  7. Understand numerical methods and their limits — discretization, accuracy, error
  8. Know when simulation breaks down — chaos, stiffness, missing physics

Core Concepts

programming, simulation, implementation, data-collection, visualization, debugging, discretization, numerical-error, time-stepping, state-update, verification

Course Structure (14 weeks)

WeekTopicMajor Assignment
1-2Programming fundamentals for systemsBuild a simple system simulation
3-4Implementing equations in codeTranslate math into code
5-6Data collection from simulationsCollect and organize simulation output
7-8Visualization and analysisPlot and interpret results
9-10Multi-component systemsImplement interacting components
11Verification and debuggingTest simulation correctness
12Numerical methods and accuracyUnderstand time step and error
13-14Integration and synthesisComplete simulation project

Tools and Languages

This course teaches systems thinking through programming, not a specific language. Python is recommended (readable, rich libraries for visualization and numerical computation), but concepts transfer to any language.

Prerequisites for Subsequent Courses

This course provides the implementation foundation needed for Stage III (Dynamic Network Simulation) and throughout the program whenever simulation is needed.

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