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Google Colab Tutorial 2025: From Beginner Basics to Advance
Rating: 3.9 out of 5(41 ratings)
2,955 students

Google Colab Tutorial 2025: From Beginner Basics to Advance

Learn to code in the CLOUD with Python coding, data science, and machine learning — no installation required and free!
Created byCode With Ebrima
Last updated 3/2025
English

What you'll learn

  • Understand what Google Colab is and why it’s valuable for cloud-based coding in 2025
  • Create, rename, and organize notebooks using Google Colab’s modern interface
  • Write, format, and run Python code using code cells and markdown text cells
  • Navigate menus like File, Edit, and Runtime with confidence
  • Import and analyze data using Pandas and NumPy
  • Upload CSV files, read data into dataframes, and perform basic analysis
  • Use advanced features like runtime types, AI assistance, and GitHub integration
  • Customize their Colab environment for better readability and efficiency
  • Collaborate with others by sharing notebooks and accessing real-time features

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Course content

1 section • 20 lectures • 35m total length

  • What is Google Colab? (2025 Edition)1:19

    Explore Google Colab as a browser-based Python coding environment with no installation and cloud-based convenience. Access free GPUs and TPUs, save automatically to Google Drive, and collaborate in real time.

  • How to Access Google Colab0:47

    Google Colab link is available in the Resources section of this lecture

  • Creating a New Notebook0:44

    Create a new notebook in Google Colab, rename it for easy reference, and replace the default untitled filename with a clear demo.

  • Personalizing Your Google Colab3:26

    Learn to personalize your Google Colab workspace by adjusting background and editor settings, including font size, font family, indentation, line numbers, and code completions in code cells.

  • Writing Your First Code in Colab0:44

    Write your first code in Colab by printing 'Hello, World!' in Python, then run the cell by clicking the play button or pressing Shift+Enter.

  • How to Add a New Code and Text Cell2:18

    Learn to navigate the Google Colab interface, add and run Python in code cells, and use text cells for explanations.

  • Exploring the File Menu3:39

    Explore the file menu in Google Colab to save, download, and upload notebooks, rename files, export as ipynb or py, print to pdf, and save copies to Google Drive.

  • Exploring the Edit Menu2:12

    Explore the edit menu in Google Colab to undo, redo, manage code cells, delete actions, and use find and replace to rename variables like name to f_name.

  • Exploring the Runtime Menu1:45

    Learn how to use Google Colab's runtime menu to control execution environments, run all or selected cells, change runtime type, choosing Python 3 or R, and manage sessions.

  • Using the Runtime Connection Menu1:09

    Explore Google Colab runtime connections, reconnect when inactive to resume with autosaved progress, and switch between Python 3 CPU and hardware accelerator options, including purchasing additional compute units.

  • Uploading Files in Google Colab2:20

    Learn to upload local files to Google Colab using code with files.upload() and via manual upload with the Files icon, including selecting, loading, and verifying uploaded csv files.

  • Importing Pandas and Reading CSV Files2:03

    Google Colab pre-installs libraries, so you can import pandas as pd and use pd.read_csv to read a csv file and inspect the data with data.head() and data.tail().

  • Advanced Runtime Connection Features1:51

    Explore advanced runtime connection features in Google Colab, including disconnecting, deleting, and reconnecting runtimes, and understanding the warnings about losing local variables and files.

  • Importing Numpy in Google Colab0:20

    Learn how to import numpy as np in Google Colab, noting that numpy is readily available and pre-installed, avoiding ModuleNotFoundError.

  • Sharing and Collaborating in Google Colab1:43

    Learn to share Google Colab notebooks, invite collaborators, set access levels (restricted or anyone with the link), copy and send sharing links for seamless collaboration.

  • Quick Revision1:06

    Revisit key Google Colab features by previewing notebooks, using Google Drive and GitHub for access, uploading demo.ipynb, and navigating to colab.google for quick revision.

  • Additional Resources & Learning Materials5:37

    Explore Google Colab's resources and learn to access blog posts, release notes, and sample notebooks while understanding free and paid plans for beginners in data science and machine learning.

  • How to Use AI Assistance in Colab0:53

    Unlock AI assistance in Colab by enabling generative AI features for code autocomplete and intelligent recommendations, with options to show inline completions or hide them.

  • Github Integration and Miscellenous Settings0:37

    Explore Colab Pro and GitHub integration, enabling importing and saving notebooks for collaborative development. Customize Colab with miscellaneous layout, snippet, and workspace preferences.

  • Conclusion & Next Steps0:31

    Master Google Colab as a powerful, customizable platform for productivity, efficiency, and collaboration. Dive into core Python concepts and hands-on coding to advance your Python journey with Code with Ebrima.

Requirements

  • No prior experience with Google Colab or Python is needed.
  • A basic understanding of how to use a web browser is helpful.
  • Learners just need an internet connection and a Google account to get started.

Description

Google Colab Tutorial 2025 — Learn how to code on the CLOUD From beginner Basics to Pro level
In this beginner-friendly course, you'll learn how to use Google Colab, a free, cloud-based coding platform that runs Python code directly in your browser — no installation needed. It's perfect for data analysis, machine learning, and deep learning, with seamless integration for popular Python libraries used in the field.

Colab requires no setup, making it ideal for beginners and professionals alike. You’ll be able to collaborate in real time, access powerful cloud-based hardware, and easily share notebooks — all within the platform. Whether you're learning Python for fun or working on serious projects, Colab offers a flexible and reliable environment for growth.

Whether you're a student, beginner programmer, or data enthusiast, this course guides you step-by-step through:

  • Creating and managing notebooks

  • Writing and executing Python code

  • Using markdown cells for notes and formatting

  • Uploading and working with datasets

  • Performing basic data analysis with Python libraries

  • Connecting Colab with version-controlled repositories

  • Exploring Colab’s AI-powered productivity tools

By the end of this course, you'll be fully confident using Google Colab for Python development, data science workflows, and even machine learning projects — all from your browser.

No installations. No headaches. Just code, run, and learn — anytime, anywhere.

Who this course is for:

  • Beginners who want to start coding without installing anything
  • Students and researchers working on data science, AI, or machine learning
  • Python developers exploring cloud-based IDEs
  • Anyone looking for a free, beginner-friendly environment to write and run Python code in 2025

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