Semantic Search API with S-BERT and Search API with RAG/LLM

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.