Free Coupon Code Semantic Search API with S-BERT and Search API with RAG/LLM 100% OFF

Free Coupon Code Semantic Search API with S-BERT and Search API with RAG/LLM 100% OFF
Free Coupon Code Semantic Search API with S-BERT and Search API with RAG/LLM 100% OFF

Udemy coupon code for Semantic Search API with S-BERT and Search API with RAG/LLM course taught by André Vieira de Lima, which has 866 students and is rated 5.0 out of 0 votes. This course is about 7 hour(s) 30 minute(s) in English and was updated on April 02, 2025. You can use this Udemy course with a free certificate and find the coupon at the bottom of this page.

Using Artificial Intelligence (NLP) to build a semantic text query API with BERT and RAG (LangChain/LLM)

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In a rich Artificial Intelligence Bootcamp, learn S-BERT and RAG(LLM) through Natural Processing Language (NLP) with Python, and develop a semantic text search engine API by solving a real problem of a purchasing analysis system.

As content:

  1. Fundamentals.
    Learn the fundamentals of Data Science;

    • Learn the fundamentals of Machine Learning;

    • Learn the fundamentals of Natural Language Processing;

    • Learn the fundamentals of Data Cleaning, Word Embendings, Stopwords, and Lemmatization;

    • Learn the fundamentals of text search by keywords and semantic text search;

  2. Practice Data Science to understand the problem, prepare the database and statistical analysis;

  3. Practical project.
    This course is divided into two modules where you will learn concepts and build a text search application in a practical way.

    1. BERT
      In this module, you will work with:

      • Python to develop the application;

      • Data cleaning techniques to prepare the database;

      • Using the SpaCy library for Natural Language Processing;

      • Generating Word Embeddings and calculating similarity for data recovery;

      • Transformers model for data recovery by context;

      • S-BERT as a semantic text search tool;

      • Flask and Flassger for developing APIs.

    2. Retrieval-augmented generation (RAG)
      In this module you will work with:

      • Python to develop the application;

      • Large Language Models (LLMs). Advanced AI models that understand and generate natural language;

      • Using the OpenAI API to build AI products

      • LangChain to build applications that use LLMs;

      • Flask and Flassger for developing APIs.

  4. Optional module: learn how to develop API with Flask.

Welcome and have fun.


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