Building a News Fact-Checker AI Agent

Jon Bennion, Manager of Applied Machine Learning at The Objective AI, guides you through building a news fact-checker AI agent from scratch.

Apr 30, 2025

Code along with us onCode Along

Building AI agents that can fact-check news articles is a powerful way to combat misinformation and provide users with reliable information. Combining large language models (LLMs), Retrieval-Augmented Generation (RAG), and API integrations allows AI engineers to create robust applications that validate news content against credible sources. Mastering these techniques equips you with the skills to build intelligent, trustworthy AI systems.

In this hands-on code-along session, Jon Bennion, Manager of Applied Machine Learning at The Objective AI, will guide you through building a news fact-checker AI agent from scratch. You’ll learn how to create a simple AI agent, combine LLMs with RAG and API calls, and test and evaluate your application’s performance. The session will also cover best practices for ensuring the quality and accuracy of your AI agent, providing you with practical experience and valuable insights. This webinar is perfect for AI engineers looking to build impactful AI tools with real-world applications.

Key Takeaways:

Learn how to create a simple AI agent for fact-checking news articles.
Discover how to combine LLMs, RAG, and API calls to build powerful AI applications.
Gain insights into testing and evaluating the quality of AI tools.

Session Resources

Topics

Artificial Intelligence

Python

DataLab

Machine Learning and AI

blog

Announcing the new DataCamp AI Assistant

Discover the DataCamp AI Assistant—a new way to reach your learning goals faster

DataCamp Team

3 min

podcast

Fake News Detection with Data Science

How can data science and deep learning be leveraged to detect fake news? Come on a journey with Mike Tamir, Head of Data Science at Uber ATG, who is building out a data science product that classifies text as news, editorial, satire, hate speech and fake news.

Hugo Bowne-Anderson

58 min

Tutorial

Detecting Fake News with Scikit-Learn

This scikit-learn tutorial will walk you through building a fake news classifier with the help of Bayesian models.

Katharine Jarmul

15 min

code-along

Building NLP Applications with Hugging Face

Perform a variety of NLP tasks from sentiment analysis to clustering with Hugging Face, and build a bot that generates marketing copy for a fashion retailer.

Jacob Marquez

code-along

Building an AI Note-taking Application

Paul-Emil Iusztin, Founder of Decoding ML, walks you through the process of building a Second Brain AI assistant from scratch.

Paul-Emil Iusztin

code-along

AI Python Zero-to-Hero: Build a Customer Feedback Analyzer

Francesca Donadoni, Curriculum Manager for Artificial Intelligence at DataCamp, guides you through building your own customer feedback analyzer.

Francesca Donadoni

See More See More