Udemy – 7 Days RAG with Python: Build Chatbots That Talk to Data 2026-7

Udemy – 7 Days RAG with Python: Build Chatbots That Talk to Data 2026-7

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Description

7 Days RAG with Python: Build Chatbots That Talk to Data is a course on how to build intelligent retrieval-augmented (RAG) chatbots using Python, published by Udemy Online Academy. This course is an intensive, project-based program that teaches developers how to build intelligent retrieval-augmented (RAG) chatbots using Python. Designed for AI engineers, Python developers, and machine learning enthusiasts, the course guides individuals through the complete process of creating AI assistants that can retrieve information from custom data sources and produce accurate, context-aware responses.

Participants will learn about document retrieval, text segmentation, embeddings, vector databases, semantic search, large language model (LLM) integration, rapid engineering, and chatbot deployment. In this hands-on, project-based course, learn how to build powerful retrieval-enhanced production applications with Python. You’ll create PDF chatbots, semantic search engines, vector database applications, and a full-fledged enterprise knowledge assistant that can answer questions using your private documents and data. By the end of the course, you’ll have completed a portfolio-ready enterprise knowledge and research assistant using Python, Streamlit, embeds, vector databases, and mods.

What you will learn in 7 Days RAG with Python: Build Chatbots That Talk to Data:

Understand how Retrieval Augmented Generation (RAG) works and when to use it instead of relying solely on a large language model.
Build Python programs that allow users to ask questions about their documents and data.
Extract, clean, and process content from PDF, text, Markdown, and CSV files.
Split documents into efficient chunks while preserving useful metadata like filenames, headings, and page numbers.
Create text embeds and store them in vector databases like ChromaDB or FAISS.
Build semantic search systems that retrieve information based on meaning rather than exact keyword matches.
Build a PDF chatbot that answers questions and displays supporting sources and page citations.
And…

Course specifications

Publisher: Udemy
Instructors: School of AI and Arjun Vaid
Language: English
Level: Introductory to Advanced
Number of Lessons: 45
Duration: 10 hours and 4 minutes

Course topics

7 Days RAG with Python: Build Chatbots That Talk to Data Content

7 Days RAG with Python: Build Chatbots That Talk to Data Prerequisites

Basic Python knowledge, including variables, functions, loops, lists, dictionaries, and importing packages, is helpful.
No previous experience with Retrieval-Augmented Generation, vector databases, embeddings, or LangChain is required.
No advanced machine learning or mathematics knowledge is required.
A computer running Windows, macOS, or Linux is required.
Python 3.10 or later should be installed.
A code editor such as Visual Studio Code, PyCharm, or Jupyter Notebook is recommended.
Learners should be comfortable installing Python packages and running basic commands in a terminal.
An internet connection may be required to install packages, download models, or access hosted AI services.
Learners may use a hosted language model API or a local model through Ollama, depending on their preferred setup.
Sample documents and starter resources can be provided during the course, so learners do not need to prepare their own dataset.
Curiosity and a willingness to build practical projects are the most important requirements.