Getting Started

COMP 536: Computational Modeling for Scientists

Author

Anna Rosen

Your Foundation for Computational Science

Before we model complex systems, we need to set up our computational laboratory. This module establishes the professional development environment and essential skills you’ll use throughout COMP 536 and your research career.

TipModule Philosophy: Tools Shape Thinking

The difference between a computational scientist and someone who codes isn’t knowledge of Python syntax — it’s mastery of the ecosystem. Version control, environment management, and command-line fluency aren’t just “nice to have” skills; they fundamentally change how you approach problems, collaborate, and think about reproducible science.

Module Overview

Command Line Interface

Master the terminal with essential commands for file management, navigation, and automation

Start Guide \(\to\)

Software Setup

Install Python with Miniforge, configure VS Code, and create your isolated course environment

Start Guide \(\to\)

Git & GitHub

Version control fundamentals, GitHub Classroom workflow, and collaboration best practices

Start Guide \(\to\)

NoteDaily Workflow Companion

Before you code, open the Scientific Software Workflow Cheatsheet. It compresses the reproducibility contract, evidence model, and debugging ladder into one page you can keep beside your editor.

Why This Order Matters

graph LR
    A[CLI Skills] --> B[Software Setup]
    B --> C[Version Control]
    C --> D[Ready for Projects]

    A1[Navigate & Execute] --> A
    B1[Run Install Commands] --> B
    C1[Use Git in Terminal] --> C
    D1[Submit Assignments] --> D

    style A fill:#e3f2fd
    style D fill:#f3e5f5

Complete these guides in order. Each builds on the previous:

  1. CLI first: Learn to navigate before installing anything.
  2. Setup second: Use your CLI skills to install tools.
  3. Git last: Apply everything to manage your code.

Learning Path

ImportantModule Goals

After completing this module in order, you will:

  • Navigate the terminal with confidence using pwd, ls, cd, and Tab completion.
  • Have a fully configured Python environment isolated from system Python.
  • Understand conda environments and why they prevent dependency conflicts.
  • Use Git for every assignment submission via GitHub Classroom.
  • Debug common issues independently using error messages.
  • Appreciate why every computational scientist relies on these tools daily.

Time Investment

Component Time
Module Total 3-4 hours (estimated)
CLI Introduction 45 minutes
Software Setup 30 minutes
Git Introduction 45 minutes
Practice 60+ minutes
Daily Practice 5-10 min/day

Common Challenges (and Solutions)

WarningExpected Hurdles

Challenge 1: “The terminal is scary” Solution: Start with just 3 commands (pwd, ls, cd). Everything else builds on these.

Challenge 2: “Command not found” errors Solution: Usually means wrong environment. Check for (comp536) in your prompt.

Challenge 3: Git says “failed to push” Solution: Someone else pushed first. Pull, resolve conflicts, then push.

Challenge 4: “This doesn’t work on Windows” Solution: Use Git Bash for Unix-like commands. We’ve noted all platform differences.

Challenge 5: “I accidentally deleted files with rm” Solution: Why we emphasize backups and teach safe deletion practices first!

Your First Week Checklist

NoteSetup Verification

Complete these milestones in order:

After CLI Guide

After Software Setup

After Git Guide

Ready for Project 1

Quick Command Reference

Command What It Does
Terminal Basics
pwd Show current directory location
ls -la List all files with details
cd folder_name Change to different directory
Tab key Autocomplete (use constantly!)
Python Environment
conda activate comp536 Enter your course environment
python script.py Run your Python code
which python Verify correct Python is active
Git Workflow
git status Check what’s changed
git add . Stage all changes
git commit -m "message" Save your work
git push Submit to GitHub

Getting Help

NoteSupport Resources

Setup Issues:

  • Read error messages carefully (they usually tell you what’s wrong).
  • Google the exact error message in quotes.
  • Check our troubleshooting sections in each guide.
  • Post on course Slack with: OS, command tried, full error.

Conceptual Questions:

  • Why do we need virtual environments?
  • How does Git track changes?
  • What’s the difference between terminal and shell? \(\to\) Great office hours questions!

Platform-Specific Issues:

  • Windows: Use Git Bash for Unix commands
  • Mac: If commands fail, check if you need to install Xcode tools
  • Linux: Usually works out of the box

Remember: Everyone struggles with setup. Once it’s working, it just works.

Module Completion

ImportantSuccess Indicators

You’re ready for Python Fundamentals when you can:

  1. Open terminal and navigate to any folder using cd and ls
  2. Activate your environment with conda activate comp536
  3. Create a Git repository, make commits, and push to GitHub
  4. Run Python scripts from the command line
  5. Fix basic issues using error messages and documentation

If you can do these five things, you have the foundation for everything in this course!

What’s Next?

After completing this module, you’ll begin the Python Fundamentals module where you’ll:

  • Write your first object-oriented simulation
  • Use the terminal skills daily for running scripts
  • Submit all work via Git and GitHub Classroom
  • Build on this foundation for the rest of your career
TipHow to Succeed in This Module

Don’t Rush: Setup problems compound. Better to spend an extra hour now than fight your environment all semester.

Practice Daily: Spend 10 minutes each day using the terminal. Muscle memory develops quickly with consistent practice.

Commit Often: Make Git commits after every small success. You can’t over-commit, but you can under-commit.

Read Error Messages: They usually tell you exactly what’s wrong. Copy the full error when asking for help.

Keep Notes: Document what worked for your specific system. You’ll need these notes again for future projects.

Remember: These tools aren’t just course requirements—they’re essential skills for any scientific research career. The more you invest in mastering them now, the more prepared you’ll be for real research challenges ahead.

Ready to begin? Start with Chapter 1: Command Line Interface \(\to\)