AI Agents for Data Analysis: Pandas and SQL Basics

Data analysis is evolving rapidly, and AI agents are at the forefront of automating complex workflows. If you want to leverage artificial intelligence to query databases and manipulate datasets, understanding agentic workflows is an essential next step. This course guides you through the foundational concepts of building AI agents tailored for data tasks. You will start by learning key terminology surrounding large language models, prompt engineering, and agent architecture. From there, you will explore how to connect these models to practical data tools like Pandas and SQL, enabling you to create systems that can interpret questions, write code, and extract insights autonomously. What you will learn: • Understand the core architecture and terminology of modern AI agents. • Apply fundamental prompt engineering techniques to guide model behavior. • Build text-based workflows that interface with SQL databases for dynamic querying. • Automate data manipulation tasks using Pandas and foundational agent patterns. • Implement basic function calling to give your AI models access to external tools. • Practice structuring predictable and reproducible data analysis pipelines. The curriculum flows from basic definitions and core AI concepts to practical, written exercises where you will integrate models with data environments. You will read through clear explanations and study code snippets that demonstrate how these systems communicate and execute tasks. Designed for beginners, data enthusiasts, and aspiring analysts, this foundational course requires no prior experience with AI development. Start reading today to unlock the potential of AI-driven data analysis.