IntroDataScience

Introduction to Data Science 📊

A beginner-friendly, hands-on introduction to modern data science tools and techniques

For: First-time coders learning data science
Location: Johannesburg SA 2026 Trainings
Duration: ~3 hours

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🎯 What You’ll Learn

By the end of this course, you’ll be able to:

• Write Python code for data analysis
• Load and manipulate data with Polars
• Create interactive visualizations with Plotly
• Use AI tools (GitHub Copilot) to help you code

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🚀 Quick Start (5 Minutes)

Prerequisites

• Required: None! This course is designed for complete beginners
• Equipment: Computer with internet (Mac, Windows, or Linux)

Setup Steps

1. Install VS Code (if you haven’t already)

   • Download and install VS Code from code.visualstudio.com
   • Install Marimo extension from Visual Studio Marketplace

2. Install UV and add to PATH (Python package manager)

   # macOS/Linux (Ubuntu or Debian)
   curl -LsSf https://astral.sh/uv/install.sh | sh
   source $HOME/.local/bin/env
   
   # Windows (PowerShell)
   powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
      
   # Should be added to PATH already, but in case
   [Environment]::SetEnvironmentVariable("Path", $env:Path + ";C:\Users\$env:USERNAME\.cargo\bin", "User")
   

   # Verify Installation
   uv --version
   

3. Install Python with UV

   uv python install
   

   # Verify Installation
   python --version
   

4. Install Git and verify installation

   # Windows (Powershell)
   winget install --id Git.Git -e --source winget
      
   # macOS
   brew install git
   
   # Linux (Ubuntu or Debian)
   apt-get install git
   

   # Verify Installation
   git --version
   

5. Clone this repository

   git clone https://github.com/quickskilling/IntroDataScience.git
   cd IntroDataScience
   

   If git doesn’t work for you, you can download the repository

6. Sync dependencies

   uv sync
   

7. Launch your first notebook

   uv run marimo edit example_notebooks/01_python_basics.py
   

📖 Need more help? Check out the detailed setup guide

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📚 Learning Path

Overview and Setup (40 minutes)

✓ Overview of Data Science and Tools ✓ Install VS Code and UV
✓ Clone the repository and sync dependencies
✓ Launch first notebook

Phase 1: Learn the Basics (1 hour)

📓 Notebook 1: Python Basics (20 min)

• Variables, data types, and operations
• Lists and dictionaries
• Control flow (if/else, loops)
• Functions

📓 Notebook 2: Data Wrangling (20 min)

• Loading data (CSV, JSON, Parquet)
• Exploring DataFrames with Polars
• Filtering, selecting, and transforming data
• Joining datasets

📓 Notebook 3: Plotting (20 min)

• Line charts and bar charts
• Scatter plots and histograms
• Customizing visualizations
• Subplots

Phase 2: Practice (1 hour)

✏️ Exercise 1: Fundamentals (20 min)

• Practice Python basics
• 8-10 hands-on exercises

✏️ Exercise 2: Basic Data Wrangling with Polars (20 min)

• Load and manipulate real datasets
• Answer questions with data

✏️ Exercise 3: Basic Plotting with Plotly (20 min)

• Create visualizations from data
• Hands-on exercises

Total Time: ~3 hours

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🛠️ Technology Stack

Our modern, industry-standard tools:

• Python - The most popular data science language
• UV ⚡ - Lightning-fast package manager
• Marimo 📓 - Reactive Python notebooks
• Polars 🐻‍❄️ - Blazing-fast data manipulation
• Plotly 📊 - Interactive visualizations

• GitHub Copilot 🤖 - AI coding assistant

  If git doesn’t work for you, you can download the repository

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📁 Repository Structure

📦 IntroDataScience/
├── 📓 example_notebooks/  → Learning notebooks (start here!)
│   ├── 01_python_basics.py
│   ├── 02_data_wrangling.py
│   └── 03_plotting.py
│
├── ✏️ exercises/           → Practice problems
│   ├── ex01_fundamentals.py
│   ├── ex02_wrangle_and_plot.py
│   └── ex03_mini_project.py
│
│
├── 📊 data/                → Sample datasets
│   └── raw/
│       ├── students.csv
│       ├── sales.json
│       └── weather.parquet
│
└── 📚 docs/                → Tool guides and documentation

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✅ Progress Tracker

Track your journey through the course:

Setup

• Install VS Code and extensions
• Install Python
• Install UV and dependencies
• Install Git and clone the repository
• Run first notebook successfully

Learn (Example Notebooks)

• 01: Python Basics (20 min)
• 02: Data Wrangling (20 min)
• 03: Plotting (20 min)

Practice (Exercises)

• Exercise 1: Fundamentals (20 min)
• Exercise 2: Basic Data Wrangling with Polars (20 min)
• Exercise 3: Basic Plotting with Plotly (20 min)

You’re Done! 🎉

• Share your work
• Keep learning with your own data

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💡 Getting Help

• Read error messages carefully - They often tell you exactly what’s wrong!
• Check the docs - Each tool we use has a guide in the /docs folder
• Ask your neighbor - Pair programming can improve efficancy and help you learn
• Ask GitHub Copilot - If you have it installed, use Copilot Chat for help
• Raise your hand - A DataThink representative will be happy to help if you get stuck

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Ready to start? Jump to example_notebooks/01_python_basics.py 🚀