Python Basics Colab Google Colab

Leo Migdal

-Nov 17, 2025, 7:50 PM

Welcome to this beginner-friendly repository! 👋 This repository contains a Google Colab Notebook that covers the fundamentals of Python programming along with some basic Data Structures and Algorithms (DSA) concepts. It is designed to help absolute beginners quickly grasp the core concepts of Python and begin their journey into programming and problem-solving. The notebook is divided into clear, easy-to-follow sections with examples, explanations, and code snippets for each topic: What is Python? Brief overview of Python and why it's popular.

Variables and Datatypes Explanation of variables and different datatypes like int, float, string, boolean, etc. An introduction to commonly used data structures and simple algorithms to build a strong foundation for problem-solving. Google Colab is a product from Google Research that allows anyone to write and execute arbitrary Python code through the browser. It's especially well-suited for machine learning, data analysis, and educational purposes. With Colab, you can leverage the power of GPUs and TPUs for free, making it a popular choice for resource-intensive tasks. When running deep-learning scripts, you will need to change from CPU to GPU.

To do this, click Runtime → Change runtime type, then select T4 GPU. Then click Save. Note: You are encouraged to sign up to Google Colab with an existing Google account. If you create a new Google account, your GPU usage may be cut off. You may find yourself doing a tutorial where the creator provides you with a link to a Google Colab link. Just like in our Fine-Tuning Embedding Models Course, we provided a link to this Google Colab book.

To run external Colab notebooks, you run them as you would any notebook you’ve built yourself. Just click the run icon that’s located to the left of the cell and it will execute the code. It’s important to run each cell in succession. 4) Most advanced programming language which is using in ML, DL, Web development, Finance, Data Science, and so on. 5) Their libraries, Packets are mostly free of cost. #Bs Intelligent Systems and Robtics #The Islamia University of Bahawalpur

Here, I am showing a basic coding example in Python. After this, I will discuss the AI, ML, DL, Computer vision, and IoT devices programming, and more In software testing, we often begin by practicing with a simple “Hello, World!” program. Similarly, in hardware, we start by blinking an LED. Coding becomes much easier once we understand its logic. Not every coder will reach the top, but…

Running Python code in the cloud without worrying about local setup is a game-changer. With the rise of collaborative and remote data science, Google Colab, often referred to as Google Notebook, has emerged as a top tool for coders, data scientists, and researchers. Google Colab offers a powerful browser-based notebook interface, making it easy to write and execute Python code from any device, anywhere. Backed by Google’s cloud infrastructure and integrated with Google Drive, it empowers you to develop and share notebooks seamlessly. Google Colab (short for Colaboratory) is a free Jupyter notebook environment that runs in the cloud and requires no setup. It supports Python and offers access to GPUs and TPUs, making it a great platform for AI, data analysis, and education.

Unlike traditional Jupyter Notebooks that require local setup via Anaconda or pip, Google Notebook is ready-to-use directly in the browser and comes pre-installed with major Python libraries like NumPy, Pandas, TensorFlow, Keras, and OpenCV. Using Google Colab over local environments offers several advantages: Google Colaboratory, often abbreviated as Colab, is a free cloud - based Jupyter notebook environment provided by Google. It allows users to write and execute Python code in the browser without the need for local installation of Python or any related libraries. This makes it an excellent choice for beginners, data scientists, and researchers who want to quickly prototype and test their Python code, especially for machine learning and data analysis tasks. In this blog, we will explore the fundamental concepts, usage methods, common practices, and best practices of using Google Colaboratory with Python.

Google Colaboratory is a hosted Jupyter Notebook service. Jupyter Notebooks are documents that contain both code and rich text elements (like markdown). Colab provides free access to computing resources, including GPUs (Graphics Processing Units) and TPUs (Tensor Processing Units) in some cases. This enables users to run computationally intensive Python code, such as neural network training, without the need for a high - end local machine. Python is one of the most popular programming languages supported in Colab. It comes pre - installed with a wide range of common Python libraries such as NumPy, Pandas, Matplotlib, and many more.

These libraries are essential for data analysis, machine learning, and scientific computing. Users can write Python code in Colab notebooks, execute it cell by cell, and view the results immediately. If you need to use a library that is not pre - installed in Colab, you can install it using the !pip install command. For example, if you want to install the seaborn library for data visualization: This will prompt you to authenticate and provide a code. After authentication, your Google Drive will be mounted at /content/drive.

You can then access your data files. Google Colab is a free Jupyter notebook that allows to run Python in the browser without the need for complex configuration. It comes with Python installed and has all the main Python libraries installed. It also comes integrated with free GPUs. In this tutorial, we will cover everything that you need to get started using Python with Google Colab. Google Colab is truly the fastest way to start using Python on any computer.

Google Colab is a browser-based product created by Google Research that allows to write and execute Python code without specific configuration. Python comes pre-installed in Google Colab. You can start using Python in Google Colab straight away.

Python Basics Colab Google Colab

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Welcome To This Beginner-friendly Repository! 👋 This Repository Contains A

Variables And Datatypes Explanation Of Variables And Different Datatypes Like

To Do This, Click Runtime → Change Runtime Type, Then

To Run External Colab Notebooks, You Run Them As You

Here, I Am Showing A Basic Coding Example In Python.