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Building LLM Applications for Structured Data Insights

Learn How to Build Smart Apps That Understand Your Data

  • Schedule

    23 – 26 June 2025

    18.30 – 21.30 (WIB)

  • Online-Interactive Learning

    Via Zoom

  • Investment

    Rp. 1.500.000

Course Summary

Retrieval-Augmented Generation (RAG) for Structured data is a method that combines retrieving relevant rows or data points from tables with generating natural language answers using a language model. The process involves converting tabular entries into embeddings, storing them in a vector database, retrieving relevant parts based on a user query, and using a generative model (like GPT or LLaMA) to produce responses. This approach enables natural language Q&A, summaries, and insight generation from structured data like CSV.

This workshop will introduce participants to the concept of RAG for structured data and walk them through the process of building their own simple pipeline. From embedding tables to generating answers using language models, this hands-on session makes it easy for anyone to get started—no advanced coding or machine learning background required.

Learning Outcomes

Upon completion of this workshop, you will be able to:

  • Understand Structured data & Pandas
  • Learn vector embedding basics
  • Experiment with vector stores (FAISS/Chroma)
  • Try simple retrieval from a Structured data
  • Plug in a language model for generation
  • Build a Q&A interface or chatbot

Syllabus

  • What is Python & Why is it Used in AI?
  • Basic Programming Concepts:
    • Variables & Data Types
    • Lists, Dictionaries, and Tuples
    • Loops and Conditional Statements
  • What is Structured Data & Why is it Important?
  • Common Formats:
    • CSV (Spreadsheet Data)
    • SQL Databases (Relational Data)
  • Importing & Handling Structured Data in Python
  • What is Generative AI?
  • How Generative AI Differs from Traditional AI
  • Types of Data Used in Generative AI:
    • Structured Data (Tables, Databases)
    • Unstructured Data (Text, Images, Audio, Video)
  • How LLMs Can Help Analyze Structured Data
  • Extracting Insights from Tables
  • Creating an AI-Powered Q&A System for Data Analysis
  • Using AI for Data Visualization & Interpretation (Optional)

STUDENT TESTIMONIALS

This testimonial video is taken after our previous Online Data Science Series: Time Series Analysis for Business Forecasting.

LEARN FROM ANYWHERE

Our learning format is online-interactive, you will feel the interactive experience as if you were present in a physical classroom. You can access the class using your Zoom account on pre-defined dates.

  • LEARN AT YOUR OWN PACE

    Zoom recording, course Books (PDF & HTML files), the dataset for practice, reference notes, and working files are accessible through our Learning Management System account.

  • PROOF YOUR MASTERY

    Show current and prospective employers of your mastery in computer vision with a signed certificate of completion.

  • CONNECT WITH LIKE MINDED PEOPLE

    Be a part of our data-passionate community with 5000+ members and 1000+ alumni.

FOR ABSOLUTE BEGINNERS

Workshops in this series are tailored to casual programmers and non-programmers that are taking their first steps into data science. It assumes no prior knowledge or academic background, and attendees will be introduced to the beautiful art of writing R / Python code to produce data visualization and build machine learning models. The workshop has a gentle learning slope that is designed with non-technical professionals and academics in mind.

Yes, you can still attend the workshop as it is a beginner-friendly workshop.

Our system will send you an email containing a link and details to join a Google Classroom.

Online learning will be conducted via Zoom.us, Link to join the Zoom Class will be announced via Google Classroom.

Learning materials can be obtain via Google Classroom

Yes, you will receive a certificate of completion.

YOUR INSTRUCTOR

Victor Nugraha

Sr. Data Science Instructor at Algoritma Data Science School

Victor is an experienced Senior Instructor at Algoritma Data Science School, renowned for his successful training sessions for prestigious organizations across various industries, such as BCA, BRI, Bank Indonesia. OCBC NISP, CIMB Niaga, DBS Bank, Lembaga Administratif Negara, and Berau Coal. With a proven track record, he specializes in product analysis and product management, showcasing his expertise in leveraging data-driven insights. Victor is highly proficient in utilizing data science tools such as R and Python to unveil valuable insights from vast datasets, enabling him to craft diverse machine learning models.