| File Name: | Build End-to-End GenAI Project: Travel AI Agent with Python |
| Content Source: | https://www.udemy.com/course/build-end-to-end-genai-project-production-ready-agent-with-python |
| Genre / Category: | Other Tutorials |
| File Size : | 666.5 MB |
| Publisher: | Sharath Raju |
| Updated and Published: | October 4, 2025 |
In this hands-on course, you’ll learn how to create your very own AI Travel Agent – an intelligent assistant that can read PDF guides, store them as embeddings, and answer user queries using Retrieval-Augmented Generation (RAG) techniques.
This course walks you through every stage of development, starting from project setup, building the Streamlit frontend, developing a FastAPI backend, connecting to a vector database (Qdrant), and integrating OpenAI or Hugging Face LLMs. By the end, you’ll not only understand how modern GenAI apps work – you’ll have your own deployed AI assistant ready to use and extend.
What You’ll Build:
- A working AI Travel Assistant that can ingest PDFs and answer travel-related questions intelligently.
- A clean and modular Python project structure suitable for real-world deployments.
- A RAG pipeline that connects ingestion, embeddings, retrieval, and LLM generation seamlessly.
- Fully deployed frontend and backend on cloud platforms such as Railway and Streamlit Cloud.
What You’ll Learn:
- How to set up and structure GenAI projects like a pro.
- Building beautiful Streamlit UIs with file upload and query blocks.
- Creating backend APIs using FastAPI with /upload and /ask endpoints.
- Understanding document ingestion, embeddings, and vector databases.
- Connecting to Qdrant to store and retrieve embeddings efficiently.
- Implementing RAG techniques to combine retrieval and generation for smarter answers.
- Integrating OpenAI and Hugging Face models with proper key management.
- Deploying your application end-to-end to the cloud.
By the end of this course, you’ll have hands-on experience with the entire GenAI development lifecycle – from idea to a fully deployed product.
Who this course is for:
- Students and beginners curious about AI applications, even with limited prior AI experience
- Aspiring GenAI Engineers looking to learn retrieval-augmented generation (RAG), embeddings, and vector databases through practical implementation.
- Developers and Python programmers who want to get hands-on with GenAI by building a real-world project.
- Indie hackers, startup founders, or no-code builders who want to create and deploy their own AI assistant or product idea.
DOWNLOAD LINK: Build End-to-End GenAI Project: Travel AI Agent with Python
FILEAXA.COM – is our main file storage service. We host all files there. You can join the FILEAXA.COM premium service to access our all files without any limation and fast download speed.
