1 Developer Tools Fundamentals
Chapter 1 has one job: make sure you can create code, run code, save code, and explain how to rerun it.
See The Workstation
Read the picture first. The whole chapter is this loop:
terminal -> project folder -> Python environment -> editor/notebook -> Git history
Do not try to master every tool now. Build one stable workstation, then reuse it in later AI projects.
Learning Order And Task List
Use this table as both the guide and the task list.
| Page | Follow-along action | Evidence to keep |
|---|---|---|
| 1.1.1 Terminal and command line | Open the terminal and run pwd, ls, cd | A short command log |
| 1.1.2 Basic terminal operations | Create, move, inspect, and remove files in a practice folder | Folder screenshot or terminal output |
| 1.1.3 Package managers | Check how your system installs tools | Tool version notes |
| 1.2.1 Git basics and 1.2.2 Git core operations | Save a first local project snapshot | One clean Git commit |
| 1.3.1 Python environment | Create a virtual environment and run Python inside it | Python version and environment command |
| 1.3.2 VS Code and 1.3.3 Jupyter | Edit code in an editor and explore in a notebook | Working editor/notebook notes |
| 1.4.1 Follow-along workshop | Combine terminal, Python, editor, notebook, and Git | Reproducible ai-learning-lab README |
The workshop stays at the end because it is the integration step: learn the pieces first, then connect them.
First Runnable Loop
Run this in a practice folder. It creates a tiny project, runs it, documents it, and commits it.
mkdir ai-learning-lab
cd ai-learning-lab
python -m venv .venv
. .venv/bin/activate
python -c "import sys; print(sys.executable)"
printf '.venv/\n__pycache__/\n' > .gitignore
printf 'print("AI learning lab is ready")\n' > hello_ai.py
printf '# AI Learning Lab\n\nActivate env: . .venv/bin/activate\nRun with: python hello_ai.py\n' > README.md
python hello_ai.py
git init
git add .gitignore README.md hello_ai.py
git commit -m "init learning lab"
Expected output:
AI learning lab is ready
If the command fails, do not erase the error. Save the command, full output, operating system, Python version, and current directory. That record is useful project evidence.
On Windows PowerShell, use .venv\Scripts\Activate.ps1 instead of . .venv/bin/activate. If your system uses python3, replace python with python3 consistently in the commands and README.
Depth Ladder
| Level | What you can prove |
|---|---|
| Minimum pass | You can create a folder, run a script, and identify the current directory and Python interpreter. |
| Project-ready | A fresh terminal can follow your README, .venv/ is ignored, and git status only shows intentional changes. |
| Deeper check | You can explain why PATH, working directory, shell, and interpreter choice change results across machines. |
Common Failures
| Symptom | First thing to check | Usual fix |
|---|---|---|
| Command not found | Is the tool installed and available in PATH? | Reopen the terminal or reinstall the tool |
| Python import fails | Are python and pip from the same environment? | Install with python -m pip install ... |
| File not found | Are you in the correct directory? | Run pwd and ls, then move to the project folder |
| Git commit fails | Is Git initialized, staged, and configured? | Run git status and set username/email if needed |
| README command fails | Did the README include every required step? | Test from a fresh terminal and update the README |
Pass Check
Move to Chapter 2 when you can answer these five questions:
- Which directory is the terminal using?
- Which Python interpreter is running your script?
- What changed since the last Git commit?
- What command reruns the project from a fresh terminal?
- Where did you record your first error and fix?
The goal is not tool perfection. The goal is a workstation stable enough for the rest of the course.