100% OFF Semantic Search API with S-BERT and Search API with RAG/LLM Coupon Code
100% OFF Semantic Search API with S-BERT and Search API with RAG/LLM Coupon Code
  • Promoted by: Anonymous
  • Platform: Udemy
  • Category: Data Science
  • Language: English
  • Instructor: André Vieira de Lima
  • Duration: 7 hour(s) 30 minute(s)
  • Student(s): 866
  • Rate 5 Of 5 From 0 Votes
  • Expired on April 02, 2025
  • Last Update: 2025/04/02
  • Price: 49.99 11.99

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

Unlock your potential with a coupon code for the "Semantic Search API with S-BERT and Search API with RAG/LLM" course by André Vieira de Lima on Udemy. This course, boasting a 5.0-star rating from 0 reviews and with 866 enrolled students, provides comprehensive training in Data Science.
Spanning approximately 7 hour(s) 30 minute(s) , this course is delivered in English and we updated the information on April 02, 2025.

To get your free access, find the coupon code at the end of this article. Happy learning!

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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