Setup Guide¶

Goal: a working environment for all 32 sessions — Python + Jupyter for Modules A–B and Ollama + n8n for Module C. Do this once, at the start of the course.

1. Install Python¶

Install Python 3.11 or newer from https://www.python.org/downloads/ (Windows: check "Add python.exe to PATH" during install).
Verify in a terminal:
```
python --version
```
(On macOS/Linux use python3 if python is not defined.)

2. Create a virtual environment¶

From the course repository root:

python -m venv .venv
# Windows:
.venv\Scripts\activate
# macOS / Linux:
source .venv/bin/activate

Your prompt should now show (.venv).

3. Install Python packages¶

pip install --upgrade pip
pip install -r requirements.txt

This installs NumPy, Pandas, Matplotlib, Seaborn, scikit-learn, Jupyter, requests, PandasAI, and the Ollama Python client.

4. Launch Jupyter¶

jupyter lab

Create a test notebook, run import numpy, pandas, matplotlib, seaborn, sklearn, and save it — if all imports succeed, the core stack works.

5. Set up Git & GitHub¶

Create a free account at https://github.com.

Configure Git once:

git config --global user.name "Your Name"
git config --global user.email "you@example.com"

Authentication: use a Personal Access Token or SSH key (https://docs.github.com/en/authentication). SSH is recommended:
```
ssh-keygen -t ed25519 -C "you@example.com"
```
and add the public key under GitHub → Settings → SSH and GPG keys.

6. Install Ollama (Module C, Week 14)¶

Download from https://ollama.com and install.
Verify and pull a small model:
```
ollama --version
ollama pull llama3.2
```

Test from Python (inside your .venv):

import ollama
print(ollama.chat(model="llama3.2", messages=[{"role": "user", "content": "Hi"}])["message"]["content"])

Any model from https://ollama.com/library works; llama3.2 is a good default.

7. Install n8n (Module C, Week 15)¶

Option A — via npx (Node.js required; install from https://nodejs.org):

npx n8n

Then open http://localhost:5678.

Option B — via Docker:

docker run -it --rm --name n8n -p 5678:5678 -v n8n_data:/home/node/.n8n docker.n8n.io/n8nio/n8n

Local runtime data is stored outside the repository (see .gitignore).

8. Verify everything¶

Run this checklist and tick each item off:

python --version → 3.11+
pip install -r requirements.txt completes
Jupyter Lab opens and a test notebook runs with all imports
git push works from a test repository
ollama pull llama3.2 completes and the Python chat test prints a reply
n8n opens at http://localhost:5678

Troubleshooting¶

Problem	Fix
`pip` not found	Activate the venv first (step 2)
Jupyter kernel uses wrong Python	`pip install ipykernel` and restart the kernel
Ollama not found in Python	Restart the terminal so PATH updates, reinstall `ollama` package
Port 5678 busy	Stop other n8n instances; `npx n8n` keeps data in `~/.n8n`