1. Create a web scraper using libraries like BeautifulSoup or Scrapy to collect data from websites. For example, you can scrape news headlines or product prices and store them in a database.

import requests
from bs4 import BeautifulSoup

def web_scraper():
url = “https://quotes.toscrape.com/”
response = requests.get(url)

soup = BeautifulSoup(response.text, 'html.parser')

quotes = soup.find_all("span", class_="text")
authors = soup.find_all("small", class_="author")

print("Quotes and Authors:")
for quote, author in zip(quotes, authors):
print(f"Quote: {quote.get_text()}")
print(f"Author: {author.get_text()}")
print("-" * 50)</code></pre>


Run the scraper



web_scraper()




Personal Finance Dashboard

Build a web-based personal finance dashboard that pulls in transaction data from APIs (like PayPal or bank APIs) and displays them in graphical formats using libraries like Plotly or Matplotlib.





Django/Flask Blog App

Build a blogging platform where users can create accounts, post articles, comment on posts, and like articles. This can be a full-stack project using Django or Flask for the backend and a simple HTML/CSS/JS front end.





AI-based Sentiment Analysis

Create a sentiment analysis tool that uses machine learning to analyze text and predict whether the sentiment is positive, negative, or neutral. You can use libraries like TextBlob or NLTK for this project.





Social Media Automation

Build a bot that can automate tasks on social media platforms (like Twitter or Instagram) using their respective APIs. The bot could post updates, follow users, or respond to comments.