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Offered By: IBMSkillsNetwork

Introduction to Agentic AI Tools

Talk to your data instead of coding SQL queries. Imagine asking a database “Who spent the most last year?” and getting an instant answer. In this course, you’ll build two working AI agents that make this possible: one that turns plain English into SQL queries for real databases, and another that lets you chat with pandas DataFrames using LangChain. Along the way, you’ll gain hands-on practice with agentic tools, seeing how they reason about data, generate queries, and make exploration intuitive.

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Course

Artificial Intelligence

At a Glance

Talk to your data instead of coding SQL queries. Imagine asking a database “Who spent the most last year?” and getting an instant answer. In this course, you’ll build two working AI agents that make this possible: one that turns plain English into SQL queries for real databases, and another that lets you chat with pandas DataFrames using LangChain. Along the way, you’ll gain hands-on practice with agentic tools, seeing how they reason about data, generate queries, and make exploration intuitive.

With the growing demand for AI tools that make data analysis more intuitive, developers and analysts can now build intelligent systems that understand plain English and interact directly with structured data. This guided project explores how to create AI agents that translate natural language questions into SQL queries and allow conversational interaction with Pandas DataFrames using LangChain. Instead of manually writing queries or inspecting tables, you’ll construct dynamic AI systems that reason about your data, generate queries, and visualize results—giving you hands-on experience with agentic AI for data exploration.

What You'll Learn

By the end of this project, you will be able to:
  • Build a natural language SQL agent: Learn to design an AI that converts English questions into SQL queries, executes them on a database, and returns structured answers.
  • Create a conversational DataFrame agent: Enable natural language interaction with Pandas DataFrames, including filtering, aggregation, and visualization using Python libraries.
  • Integrate LangChain with AI and data tools: Connect your agents to IBM Watsonx, MySQL, and Python’s data ecosystem to handle real-world datasets effectively.
  • Implement reasoning and prompt strategies: Structure prompts and AI reasoning to ensure accurate query generation, meaningful responses, and actionable insights.

Who Should Enroll 

  • Data analysts and engineers who want to automate SQL querying and data exploration using AI agents.
  • Python developers aiming to build intelligent tools for interacting with databases and in-memory datasets.
  • Technical learners looking to understand agentic AI workflows for structured data applications.

Why Enroll

This project bridges the gap between data analysis and AI automation, giving you the skills to build agents that understand your questions and work with your data directly. You’ll gain practical experience integrating LangChain with AI models, SQL databases, and Pandas DataFrames, plus the confidence to expand these agents into more complex analytical workflows. By the end, you won’t just understand natural language data agents—you’ll have fully functioning tools you built yourself.


What You'll Need 

To get the most out of this project, you should have a working knowledge of Python, Pandas, and basic SQL. Familiarity with AI models or LangChain is helpful but not required. All dependencies are pre-configured in the environment, and the project runs best on current versions of Chrome, Edge, Firefox, or Safari.

Estimated Effort

1 Hour

Level

Beginner

Skills You Will Learn

AI, AI Agent, LangChain, LLM, Machine Learning, Natural Language Query

Language

English

Course Code

AI0149EN

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