Udemy

Natural Language Processing , LLM with Python

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  • 206 Students
  • Updated 8/2025
4.3
(11 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
10 Hour(s) 47 Minute(s)
Language
English
Taught by
Rithesh Sreenivasan
Rating
4.3
(11 Ratings)

Course Overview

Natural Language Processing , LLM with Python

Learn NLP concepts with practical implementation using Python, TensorFlow, PyTorch. Learn about LLMs

In this course you will be learning about Natural Language Processing (NLP) from an experienced professional. Giving machines the capacity to find meaning in unstructured data pulled from natural language holds notable promise. By 2025, the global NLP market is expected to reach over $34 billion, growing at a CAGR of 21.5% and there would be high demand for NLP skills. In this course I cover length and breadth of topics in NLP. I explain NLP concepts in a simple way along with practical implementation in Python using libraries like NLTK, spaCy, TensorFlow and PyTorch. I also discuss various topics like text pre-processing, text classification, text summarization, topic modelling and word embeddings. I also cover NLP applications in various domains like healthcare, finance. I am sure this course should help you in getting started and also become proficient in NLP


  • In this video course you will learn the following about Natural Language Processing:

  • Introduction to NLP

  • Its Applications in domains like finance and healthcare

  • Stemming and Lemmatimzation with NLTK and spaCy

  • TF-IDF, Bag of Words Representation

  • Named Entity Recognition with spaCy in python

  • Custom Named Entity Recognition using spaCy v3 library

  • Word2Vec model and custom word2vec model in python

  • Exploratory data analysis on text dataset using python

  • Text Clustering

  • Text Classification with Neural network using Tensorflow in Python

  • Text Classification with Convolutional Neural Network( CNN) using Tensorflow in Python

  • Text Classification with Long Short Term memory( LSTM) networks using Tensorflow in Python

  • Text Classification using PyTorch library

  • Text Classification using BERT Transformers

  • Text Classification using spaCy v3 library

  • Zero shot text classification using HuggingFace

  • LDA topic modelling

  • Top2Vec Topic Modelling

  • BERTopic Topic Modelling

  • Extractive Text Summarization using gensim and python

  • Abstractive Text Summarization using Google PEGASUS

  • Extractive Question Answering with HuggingFace

  • Aspect Based Sentiment Analysis

  • HayStack Question Answering Demo

  • ChatGPT

  • ChatGPT use cases

  • How to fine tune LLMs

  • RAG

  • RAG based Chatbots


For advanced NLP content check out my Youtube Channel

Content will be constantly updated


Course Content

  • 9 section(s)
  • 39 lecture(s)
  • Section 1 Introduction to Natural Language Processing and applications in various domains
  • Section 2 Basics of Natural Language Processing
  • Section 3 Named Entity Recognition
  • Section 4 Text Clustering and Classification
  • Section 5 Topic Modelling Techniques
  • Section 6 Text Summarization, Extractive Question Answering
  • Section 7 Large Language Models
  • Section 8 Fine tuning LLMs
  • Section 9 Agents

What You’ll Learn

  • Concepts of Natural Language Processing and its Applications across various domains
  • Pratical implementation of Natural Language Processing Technqiues using Python, TensorFlow, PyTorch, Transformers, spaCy and gensim libraries
  • Understand how to approach and solve NLP problems
  • Understand how to use advanced NLP models like BERT
  • Understand LLM's and how they can be used for various use cases


Reviews

  • G
    Gopalakrishnan Kothandam
    5.0

    Hidden Gem. Great course and content. would love to learn more project based videos in the future.

  • P
    Paola Ghione
    5.0

    Spectacular and very well explained!

  • L
    Luciano Ferrara
    2.0

    Course content is even fine but the person does not explain the fundamentals of each topic and even when he goes through the code, he does not explain all the code. I won't advice this course to novices. Indeed, I didn't even complete it and bought another one (much much better). Make sure you spend more time on each topic with easier example, otherwise the course is useless or not understandable!

  • M
    Muhamad Arif bin Hashim
    4.0

    Very good intro

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