Create an AI agent to plot your data using natural language
Use LangChain, Llama 3.3, and pandas to transform your data into interactive, visual conversations. Learn to build a conversational agent that dynamically generates data visualizations from natural language queries. Enhance decision-making with timely insights and make complex data analysis accessible to all team members. Improve your data-driven strategies with cutting-edge conversational AI and visualization tools. Navigate and manipulate large datasets using conversational queries, preparing you for advanced data analysis scenarios.
4.6 (226 Reviews)

Language
- English
Topic
- Artificial Intelligence
Enrollment Count
- 1.00K
Skills You Will Learn
- LLM, Pandas, Embeddable AI, LangChain
Offered By
- IBMSkillsNetwork
Estimated Effort
- 30 minutes
Platform
- SkillsNetwork
Last Update
- January 4, 2026
Overview
Objective
- Create interactive data agents: Build conversational agents using LangChain and Llama 3.3 that can understand and respond to user queries about data stored in CSV files.
- Implement dynamic data visualizations: Learn to dynamically generate data visualizations in response to conversational queries, enabling immediate visual insights into data patterns and trends.
- Simplify data analysis: Develop skills to perform complex data analysis tasks simply by asking questions, making data analytics accessible to non-experts.
What you'll need

Language
- English
Topic
- Artificial Intelligence
Enrollment Count
- 1.00K
Skills You Will Learn
- LLM, Pandas, Embeddable AI, LangChain
Offered By
- IBMSkillsNetwork
Estimated Effort
- 30 minutes
Platform
- SkillsNetwork
Last Update
- January 4, 2026
Instructors
Kang Wang
Data Scientist
I was a Data Scientist in the IBM. I also hold a PhD from the University of Waterloo.
Read moreWojciech "Victor" Fulmyk
Data Scientist at IBM
Wojciech "Victor" Fulmyk is a Data Scientist and AI Engineer on IBM’s Skills Network team, where he focuses on helping learners build expertise in data science, artificial intelligence, and machine learning. He is also a Kaggle competition expert, currently ranked in the top 3% globally among competition participants. An economist by training, he applies his knowledge of statistics and econometrics to bring a distinctive perspective to AI and ML—one that considers both technical depth and broader socioeconomic implications.
Read moreContributors
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.
Read more