By - Data Science Dojo

Building a Data Analytics Agent using LLMs

Building a Data Analytics Agent using LLMs

Data Science Dojo

0 mins
363+ students

📝 About This Course

As LLMs continue to redefine how we work with data, building your own AI-powered analytics assistant is no longer reserved for experts or enterprises. In this session, we’ll show you how to create a fully functional data analytics agent — using only free and open-source tools. You’ll learn how to connect an LLM to your own datasets and enable natural language querying, auto-generated insights, and visualizations — all without paid platforms or complex coding. Think of it as giving your data a chat interface: ask questions in plain English and get instant answers, charts, or summaries, powered by your custom-built AI agent. What We Will Cover: - How LLMs are reshaping data analytics — from static dashboards to dynamic conversations - Step-by-step guide to building your own analytics agent using open-source tools - Live demo: Querying data, generating visual insights, and summarizing trends with an LLM - Real-world use cases in business intelligence, reporting, and decision-making - Tips to make your agent accurate, scalable, and user-friendly for non-technical users #DataAnalytics #LLMAgent #OpenSourceAI #LLMTools #DataAssistant #NoCodeAI #DataScienceDojo #BuildWithAI -------------- 👉 Learn more about Data Science Dojo here: https://datasciencedojo.com/ 👉 Watch the latest video tutorials here: https://datasciencedojo.com/tutorials/ 👉 See what our past attendees are saying here: https://datasciencedojo.com/data-scie... -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 8000+ employees from over 2000+ companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- 🔗 Subscribe to our newsletter for data science content & infographics: https://datasciencedojo.com/newsletter/

🚀 What You'll Learn

Complete understanding of the topic

Hands-on practical knowledge

Real-world examples and use cases

Industry best practices

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