Udemy – Build End-to-End GenAI Project: Travel AI Agent with Python

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

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