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Build a LangChain-based AI-powered Data Analysis Assistant

BeginnerGuided Project

Learn LangChain tools and agents while developing a data science assistant to automate tasks from exploring CSVs to training ML models. This project guides you through creating a natural language interface that makes data analysis accessible to non-technical users. Build specialized tools that handle everything from listing available datasets to generating statistics and evaluating machine learning models. Learn how AI agents interpret user requests, select appropriate tools, and execute complex data workflows through conversation.

Language

  • English

Topic

  • Artificial Intelligence

Skills You Will Learn

  • Generative AI, Python, Machine Learning, AI Agent, LLM

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 45 minutes

Platform

  • SkillsNetwork

Last Update

  • April 23, 2025
About this Guided Project
Imagine having a data analyst at your fingertips who understands natural language and can perform complex analyses without requiring you to write a single line of code. What if you could simply ask questions about your data and receive immediate insights, visualizations, and even predictive models? This is the power of combining language models with specialized data science tools.

In this hands-on lab, you'll build a conversational AI system that makes data science accessible to everyone in your organization—from marketing specialists analyzing customer segments to executives exploring sales trends, all without technical barriers.

Project Overview

This lab teaches you to create an intelligent assistant that handles the entire data workflow through natural language requests:
1️⃣ Data Discovery & Exploration - Automatically identify available datasets, summarize their structure, and provide quick statistics
2️⃣ Analysis & Visualization - Transform requests like "Show the relationship between customer age and spending" into visualizations
3️⃣ Predictive Modeling - Train and evaluate machine learning models through conversation
4️⃣ Context Management - Maintain conversation history to enable follow-up questions and complex analyses

By connecting specialized LangChain tools through an agent executor, you'll create a seamless experience where users can move from raw data to actionable insights using only conversation.

What You'll Learn

By completing this lab, you will:
  • Design effective tool-based agents that reason about when to use specific data functions
  • Build a collection of specialized tools for different data science tasks
  • Create multi-step workflows that maintain context across analyses
  • Implement natural language interfaces to technical data processes
  • Learn how to handle ambiguous user requests with clarification techniques

Who Should Do This Lab

This project is ideal for:
  • Developers looking to build practical AI applications with immediate business value
  • Data scientists wanting to make their expertise available to non-technical colleagues
  • Technical leaders exploring how AI can democratize data-driven decision making
  • AI enthusiasts interested in creating assistants that solve real-world problems
No advanced ML expertise required—basic Python knowledge and curiosity about AI applications are all you need.

What You Need

✅ A browser to access the lab environment
✅ Basic Python knowledge (understanding functions and data structures)
✅ Familiarity with data concepts (CSV files, simple statistics, basic ML terms)

By the end of this project, you'll have built an AI assistant that transforms how people interact with data—enabling anyone to ask questions and receive insights without writing code.

Instructors

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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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

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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Contributors

Wilbur Elbouni

Software Developer

I think computers are pretty cool!

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