Udemy
    •  
    •  
    •  
    •  
    •  
    •  
    •  
    •  
Turn what you know into an opportunity and reach millions around the world.
Learn More
Your cart is empty.
Keep shopping
Python for NLP: The First Step to Text Analysis
Rating: 4.3 out of 5(396 ratings)
17,403 students

Python for NLP: The First Step to Text Analysis

A Practical Guide to Text Processing: Master the First Step of NLP with Python, Regular Expressions, and NLTK.
Created byAnalytics Vidhya
Last updated 9/2025
English
English [Auto],

What you'll learn

  • Learn Basics of Natural Language Processing (NLP)
  • Learn to use Regular Expressions to extract patterns from text
  • Perform Text pre-processing
  • Perform Text classification
  • Reading and working with text data using Python

Course content

4 sections • 14 lectures • 49m total length

  • Welcome to the Course0:45
  • About the Course1:36

    Explore the fundamentals of natural language processing, its data-centric applications—from search and translation to news categorization and conversational systems—and how to implement them with Python.

  • Introduction to Natural Language Processing6:01

    Explore natural language processing basics, contrasting structured and unstructured datasets, with X data from social media; apply NLP to business needs like sentiment, automatic categorization, and patient risk.

  • Exercise : Introduction to Natural Language Processing
  • Python for Data Science (Optional)0:04

Requirements

  • This course requires you to know Machine Learning.
  • Familiarity with Python would be an added advantage.
  • There is no requirement of past experience in NLP.

Description

Do you want to build AI systems that can understand, analyze, and generate human language?

Welcome to the our course! This course is the culmination of your journey into the foundational world of Natural Language Processing (NLP). We will focus on the most crucial and practical first step of any NLP project: Text Processing.

You'll get hands-on experience with the essential tools and techniques for handling raw text data. We'll start by mastering Regular Expressions (Regex), an indispensable skill for pattern matching and data cleaning. Then, we will move on to core text normalization techniques like tokenization and learn how to perform linguistic analysis using Part-of-Speech (POS) tagging and grammar parsing.

The final section of this course is all about application. You will learn to use the powerful Natural Language Toolkit (NLTK) to implement everything you've learned. By the end, you'll be able to transform unstructured text into a format suitable for machine learning, culminating in the creation of your very own basic text classification model.

This course is your complete guide to the basics of NLP.  It will not only give you a strong theoretical understanding but also provide the practical skills you need to confidently tackle your own text-based data science projects.

Who this course is for:

  • Beginner Data Science Professionals interested in Natural Language Processing
  • Python Developers
  • Data Scientists

Report abuse