Learn GOOGLE-COLAB with Real Code Examples

Updated Nov 26, 2025

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Explain

Runs Python code in a browser-based notebook interface.

Supports rich text, code cells, and visualizations.

Provides free access to GPUs and TPUs for computation-heavy tasks.

Allows sharing notebooks via Google Drive or public links.

Encourages collaborative programming, data analysis, and research.

Core Features

Jupyter-like notebook editor in the browser

Execute Python code in cells

Access to Google Drive for reading/writing data

GPU/TPU runtime selection

Collaboration with multiple users in real-time

Basic Concepts Overview

Notebook - interactive document with code, text, and visualizations

Cell - individual code or text block

Kernel - Python execution engine

Runtime - compute resources including CPU, GPU, TPU

Output - result of code cell execution displayed inline

Project Structure

Notebook consists of sequential cells

Cells can contain code or markdown

Data stored in Google Drive or uploaded locally

Supports importing Python scripts and modules

Output displayed directly below each code cell

Building Workflow

Open Google Colab in a browser

Create a new notebook or open an existing one

Write Python code in cells

Select runtime (CPU, GPU, TPU) if needed

Run code cells, visualize results, and save/share notebook

Difficulty Use Cases

Beginner: learn Python basics in a notebook

Intermediate: analyze datasets with pandas and matplotlib

Advanced: build and train ML models using TensorFlow or PyTorch

Expert: optimize code for GPU/TPU execution

Instructor: create interactive tutorials and demos

Comparisons

Colab vs Deno Playground -> Colab: Python/ML focus; Deno: JS/TS scripting

Colab vs Rust Playground -> Colab: data science and ML; Rust: systems programming

Colab vs Jupyter Notebook -> Colab: cloud-hosted with free GPUs; Jupyter: local setup

Colab vs Replit -> Colab: notebook/ML focus; Replit: multi-language IDE

Colab vs Kaggle Kernels -> Colab: collaborative notebooks; Kaggle: dataset competitions + notebooks

Versioning Timeline

2017 - Google Colab launched publicly

2018 - Added GPU support

2019 - TPU runtime introduced

2020–2023 - Enhanced collaboration and Drive integration

2024–2025 - Continuous updates for performance and ML libraries

Glossary

Notebook - interactive Python document

Cell - code or text block