Learn Google-colab - 10 Code Examples & CST Typing Practice Test
Google Colab is a cloud-based Jupyter notebook environment that allows users to write, execute, and share Python code in the browser. It provides free access to GPUs and TPUs, making it ideal for machine learning, data analysis, and scientific computing.
View all 10 Google-colab code examples →
Learn GOOGLE-COLAB with Real Code Examples
Updated Nov 26, 2025
Code Sample Descriptions
Hello World in Google Colab (Python)
print("Hello World")
A simple Python cell in Google Colab printing 'Hello World'.
Simple TensorFlow in Google Colab
import tensorflow as tf
hello = tf.constant("Hello Colab!")
print(hello.numpy().decode("utf-8"))
Using TensorFlow in Colab to create a basic constant and run it.
NumPy Array Example in Colab
import numpy as np
arr = np.array([[1,2,3],[4,5,6]])
print(arr.shape)
Create a NumPy array and print its shape.
Matplotlib Plot in Colab
import matplotlib.pyplot as plt
x = [1,2,3,4]
y = [10,20,25,30]
plt.plot(x,y)
plt.title('Line Graph')
plt.show()
Plot a simple line graph using matplotlib.
Pandas DataFrame Example in Colab
import pandas as pd
data = {'Name':['Alice','Bob'],'Age':[25,30]}
df = pd.DataFrame(data)
df
Create a Pandas DataFrame and display it.
Seaborn Plot Example in Colab
import seaborn as sns
import numpy as np
import pandas as pd
data = pd.DataFrame({'x': np.random.rand(50), 'y': np.random.rand(50)})
sns.scatterplot(x='x', y='y', data=data)
Create a Seaborn scatter plot with random data.
Interactive Widgets in Colab
from ipywidgets import IntSlider
slider = IntSlider(value=5, min=0, max=10, step=1)
slider
Create a simple slider widget using ipywidgets.
PyTorch Tensor Example in Colab
import torch
tensor = torch.randn(3,3)
print(tensor.shape)
Create a tensor in PyTorch and print its shape.
Markdown Cell Example in Colab
# Hello Colab
This is a **Markdown** cell in Google Colab.
A Markdown cell displaying formatted text.
SymPy Symbolic Math in Colab
from sympy import symbols, expand
x, y = symbols('x y')
expr = (x + y)**2
expand(expr)
Define symbols and perform symbolic math using SymPy.
Frequently Asked Questions about Google-colab
What is Google-colab?
Google Colab is a cloud-based Jupyter notebook environment that allows users to write, execute, and share Python code in the browser. It provides free access to GPUs and TPUs, making it ideal for machine learning, data analysis, and scientific computing.
What are the primary use cases for Google-colab?
Learning Python programming. Machine learning and deep learning experiments. Data analysis with pandas, NumPy, and visualization libraries. Collaborative notebook sharing for tutorials and research. Prototyping scripts requiring GPU/TPU acceleration
What are the strengths of Google-colab?
No local installation required. Immediate execution of Python code. Supports GPU/TPU acceleration for ML tasks. Rich visualization support for plots and charts. Easily shareable notebooks for collaboration
What are the limitations of Google-colab?
Limited session runtime (12 hours for free users). Requires internet connection. Not suitable for deploying production applications. Limited persistent storage; must save to Drive or GitHub. Heavy computations may be throttled in free tier
How can I practice Google-colab typing speed?
CodeSpeedTest offers 10+ real Google-colab code examples for typing practice. You can measure your WPM, track accuracy, and improve your coding speed with guided exercises.