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Introduction to Agentic AI Tools

BeginnerCourse

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.

Language

  • English

Topic

  • Artificial Intelligence

Skills You Will Learn

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

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 1 hour

Platform

  • SkillsNetwork

Last Update

  • October 2, 2025
About this Course
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.

Instructors

Tenzin Migmar

Data Scientist

Hi, I'm Tenzin. I'm a data scientist intern at IBM interested in applying machine learning to solve difficult problems. Prior to joining IBM, I worked as a research assistant on projects exploring perspectivism and personalization within large language models. In my free time, I enjoy recreational programming and learning to cook new recipes.

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Joseph Santarcangelo

Senior Data Scientist at IBM

Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.

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Wojciech "Victor" Fulmyk

Data Scientist at IBM

I am a data scientist and economist with a strong background in econometrics, time series analysis, causal inference, and statistics. I stand out for my ability to combine technical expertise with clear communication, turning complex data findings into practical insights for stakeholders at every level. Follow my projects to learn about data science principles, machine learning algorithms, and artificial intelligence agents.

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Kang Wang

Data Scientist

I was a Data Scientist in the IBM. I also hold a PhD from the University of Waterloo.

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Ricky Shi

Data Scientist at IBM

Ricky Shi is a Data Scientist at IBM, specializing in deep learning, computer vision, and Large Language Models. He applies advanced machine learning and generative AI techniques to solve complex challenges across various sectors. As an enthusiastic mentor, Ricky is committed to helping colleagues and peers master technical intricacies and drive innovation.

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Faranak Heidari

Data Scientist at IBM

Detail-oriented data scientist and engineer, with a strong background in GenAI, applied machine learning and data analytics. Experienced in managing complex data to establish business insights and foster data-driven decision-making in complex settings such as healthcare. I implemented LLM, time-series forecasting models and scalable ML pipelines. Enthusiastic about leveraging my skills and passion for technology to drive innovative machine learning solutions in challenging contexts, I enjoy collaborating with multidisciplinary teams to integrate AI into their workflows and sharing my knowledge.

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Contributors

Kunal Makwana

Data Scientist

I’m a passionate Data Scientist and AI enthusiast, currently working at IBM on innovative projects in Generative AI and machine learning. My journey began with a deep interest in mathematics and coding, which inspired me to explore how data can solve real-world problems. Over the years, I’ve gained hands-on experience in building scalable AI solutions, fine-tuning models, and leveraging cloud technologies to extract meaningful insights from complex datasets.

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Karan Goswami

Data Scientist at IBM

I am a dedicated Data Scientist and an AI enthusiast, currently working at IBM's Skills Builder Network. Learning how some simple mathematical operations could be used to make predictions and discover patterns sparked my curiosity, leading me to explore the exciting world of AI. Over the years, I’ve gained hands-on experience in building scalable AI solutions, fine-tuning models, and extracting meaningful insights from complex datasets. I'm driven by a desire to apply these skills to solve real-world problems and make a meaningful impact through AI.

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