AI Analyst LAB

Welcome! This repository contains the course material for AI Analyst LAB, a hands-on course on using AI as a data analyst, by DataKolektiv.

Lecturer: Goran S. Milovanović, PhD, Chief Scientist & Owner, DataKolektiv

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What this README is for

This README walks you through the one-time setup of getting the course code onto your computer. After this, every week your instructor will add new sessions, and you will just run a single command (git pull) to update your local copy.

If you have never used GitHub, Git, or a terminal before, do not worry — every step is explained, and you cannot break anything by following the instructions. Plan to spend about 5 minutes on this.

If you get stuck for more than a few minutes on any step, contact your instructor — do not try to improvise.

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A two-minute glossary (for absolute beginners)

If any of these words feel unfamiliar, read them once and move on. They will start to make sense as you do each step.

• GitHub — a website that stores code and files. Think of it as Google Drive for code, plus a complete history of every change ever made.
• Repository (or "repo") — a project folder on GitHub. The page you are reading right now is the README of the AI Analyst LAB repository.
• Git — a free program that runs on your computer. Git is what talks to GitHub and downloads or uploads files for you. GitHub is the website; Git is the program — different things.
• Clone — the act of making a copy of a GitHub repository onto your computer. You do this once, at the start.
• Pull — the act of checking GitHub for new changes and downloading them. You will do this every time the instructor announces new course material.
• Terminal / PowerShell — a window where you type commands instead of clicking. On Windows it is called PowerShell. On macOS and Linux it is called Terminal. Do not be intimidated — every command in this guide can be copied and pasted.

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What you will do (overview)

You will go through three numbered steps:

1. Install Git on your computer (skip if you already have it).
2. Clone the AI Analyst LAB repository onto your computer.
3. Learn how to pull updates later in the course.

Because this repository is public, you do not need a GitHub account, an invitation, or a password to clone it.

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Step 1 — Install Git (skip if you already have it)

Open your terminal

• Windows: type "PowerShell" in the Start menu and click Windows PowerShell.
• macOS: press CMD + SPACE, type "Terminal", and press ENTER.
• Linux: press CTRL + ALT + T (or open Terminal from your application launcher).

Check whether Git is installed

In your terminal, type:

git --version

and press ENTER.

• If you see something like git version 2.50.x, you already have Git — skip to Step 2.
• If you see command not found or 'git' is not recognized, continue below.

Install Git

Windows

1. Open https://git-scm.com/downloads/win in your browser.
2. Click 64-bit Git for Windows Setup (under "Standalone Installer") to download the installer.
3. Run the downloaded .exe file. Click Next through every screen with the default options, then Install, then Finish.

macOS

The easiest way is via Homebrew. If you do not have Homebrew yet, install it by pasting this command into Terminal and pressing ENTER:

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

Follow the on-screen instructions (you will be asked for your macOS password). Once Homebrew is installed, run:

brew install git

Linux (Ubuntu / Debian)

sudo apt update
sudo apt install -y git

After installing

Close your terminal and open a new one — this is important, because the new terminal needs to pick up the updated environment. Then run git --version again to verify.

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Step 2 — Clone the repository

This is the step where the course code lands on your computer.

1. Open a new terminal.

2. Navigate to the folder where you want the course code to live. We recommend your home folder.

   • Windows:

     cd C:\Users\<your-name>
     

     Replace <your-name> with your Windows username.

     How to find your Windows username: open File Explorer → click This PC → Users. The folder names you see inside Users are usernames; one of them is yours (the folder that contains your Documents, Downloads, etc.).

   • macOS / Linux:

     cd ~
     

     The ~ symbol means "my home folder".

3. Run the clone command:

   git clone https://github.com/datakolektiv/AI_AnalystLAB.git
   

4. After a few seconds, you should see output similar to:

   Cloning into 'AI_AnalystLAB'...
   remote: Enumerating objects: ...
   Receiving objects: 100% ...
   

   When your terminal prompt comes back, the clone is complete.

5. Verify a new folder named AI_AnalystLAB appeared:

   • Windows: type dir and press ENTER.
   • macOS / Linux: type ls and press ENTER.

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Step 3 — Pulling future updates

Whenever your instructor adds new course material, you do not clone the repository again. Instead, you "pull" the new changes into your existing folder.

Open your terminal and run:

cd AI_AnalystLAB
git pull

If you opened a new terminal session and cd AI_AnalystLAB does not work, use the full path:

• Windows: cd C:\Users\<your-name>\AI_AnalystLAB
• macOS / Linux: cd ~/AI_AnalystLAB

That is all. No password, no token — git pull just downloads the latest changes.

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Common things that go wrong

• git: command not found or 'git' is not recognized — Git is not installed yet, or your terminal has not picked it up. Close the terminal, open a new one, and try again. If that still does not work, go back to Step 1.
• fatal: destination path 'AI_AnalystLAB' already exists and is not an empty directory — you already cloned the repository. Either skip the clone and run git pull instead (Step 3), or delete the existing AI_AnalystLAB folder and re-run the clone.
• Could not resolve host: github.com — your computer cannot reach GitHub. Check your internet connection and try again.

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What's next?

Once you have the AI_AnalystLAB folder on your computer:

1. Open the Session00 sub-folder.
2. Open the file AI_AnalystLAB00.ipynb — this is the Session 00 notebook.
3. Follow the instructions inside it to install Python, set up a virtual environment, install the course packages, and run a small test that confirms everything works.

The Session 00 notebook is the next step after this README. If you cannot open .ipynb files yet, do not worry — the notebook itself will tell you how to install Visual Studio Code, which is the program we use to read and run notebooks.

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Course details

• Course: AI Analyst LAB
• Year: 2026
• Lecturer: Goran S. Milovanović, PhD, Chief Scientist & Owner, DataKolektiv
• Contact: hello@datakolektiv.com
• License: GPLv3