In the Data Science and AI world, your model is only as good as your data. While many practitioners rely heavily on pre-cleaned datasets from Kaggle, real-world problems demand fresh, dynamic, and diverse data. That’s where APIs come in, offering access to constantly updated data streams from platforms you use daily. In this article, we’ll explore 5 powerful and completely free APIs that you can use for real-time data collection for your next project.
5 Free APIs for Data Collection
Below are 5 powerful and completely free APIs that you can use for real-time data collection for your next project.
Spotify Web API
If you’re building a recommendation system, analyzing audio features, or working on user preference modelling, Spotify’s API is for you.
It offers access to millions of songs, artists, albums, playlists, audio features (like tempo, energy, danceability), user playlists (with permissions), and more.
I once built a mood-based music recommendation system using Spotify’s audio features. By clustering songs based on features like energy and valence, I could suggest the perfect playlist for a user’s mood.
Here’s an example of using the Spotify Web API to build a Music Recommendation System.
NewsAPI
The NewsAPI is perfect for text analysis, sentiment detection, event detection, or even building an AI-powered news dashboard.
It offers aggregated headlines and full articles from thousands of news sources across topics like tech, finance, sports, politics, etc.
I once used it to create a real-time topic classifier that could group news articles into broader categories using NLP techniques like TF-IDF + KMeans or LDA.
Here are some project ideas you can build using this API:
- News sentiment dashboard
- Breaking news detection model
- Media bias analysis across sources
YouTube Data API
YouTube Data API is great for projects involving content recommendation, video trend analysis, or engagement forecasting.
It offers access to video metadata, comments, channel stats, likes/dislikes, and search queries. You can also analyze comment sentiment or build YouTube analytics tools.
I once analyzed trending videos over 6 months to find what types of titles, lengths, or tags performed best in tech and education categories. It’s ideal for time series or classification modelling.
Here’s an example of using the YouTube Data API for Data Analysis.
GitHub API
This is your go-to API if you’re building developer tools, analyzing open-source trends, or working on project popularity metrics.
It offers data about repositories, commits, pull requests, stars, forks, contributors, and issues. It’s a goldmine for social coding behaviour and time series patterns.
I once built a dashboard showing the health and activity of trending ML repos, tracking forks, issues closed, contributor growth, and weekly commits. Great for GitHub analytics and portfolio insights.
Here’s an example of using the GitHub API for building a Code Generation Model.
Yahoo Finance API
Yahoo Finance API is ideal for time series forecasting, portfolio simulation, or market trend analysis.
It offers historical stock prices, dividends, stock info, company financials, and news, all without needing an official API key, thanks to yfinance.
I built a stock prediction app using LSTM, where I fetched daily closing prices and volumes using yfinance. It’s super handy for financial modelling and quantitative analysis.
Here’s an example to use this API for collecting data for the task of Portfolio Optimization.
Summary
Most tutorials give you toy datasets, but real-world projects need dynamic, messy, and contextual data. These 5 APIs will allow data collection directly from platforms that people use every day, giving your models real value and real impact. I hope you liked this article on 5 powerful and completely free APIs that you can use for real-time data collection for your next project. Feel free to ask valuable questions in the comments section below. You can follow me on Instagram for many more resources.
